Image Deblocking Scheme for JPEG Compressed Images Using an Adaptive-Weighted Bilateral Filter

Transcription

1 J Inf Pocess Syst, Vol.1, No.4, pp.631~643, Decembe ISSN X (Pint) ISSN X (Electonic) Image Deblocking Scheme fo JPEG Compesse Images Using an Aaptive-Weighte Bilateal Filte Liping Wang*, Chengyou Wang*, Wei Huang**, an Xiao Zhou* Abstact Due to the block-base iscete cosine tansfom (BDCT), JPEG compesse images usually exhibit blocking atifacts. When the bit ates ae vey low, blocking atifacts will seiously affect the image s visual quality. A bilateal filte has the featues fo ege-peseving when it smooths images, so we popose an aaptiveweighte bilateal filte base on the featues. In this pape, an image-eblocking scheme using this kin of aaptive-weighte bilateal filte is popose to emove an euce blocking atifacts. Two paametes of the popose aaptive-weighte bilateal filte ae aaptive-weighte so that it can avoi ove-bluing unsmooth egions while eliminating blocking atifacts in smooth egions. This is achieve in two aspects: by using local entopy to contol the level of filteing of each single pixel point within the image, an by using an impove blin image quality assessment (BIQA) to contol the stength of filteing iffeent images whose blocking atifacts ae iffeent. It is pove by ou expeimental esults that ou popose image-eblocking scheme povies goo pefomance on eliminating blocking atifacts an can avoi the ove-bluing of unsmooth egions. Keywos Image Deblocking, Aaptive-Weighte Bilateal Filte, Blin Image Quality Assessment (BIQA), Local Entopy 1. Intouction Block-base iscete cosine tansfom (BDCT) coing has been wiely aopte by the cuent mainsteam image/vieo compession stanas an technologies because of its excellent popeties of enegy compaction an ecoelation. Fo example, JPEG [1] an H.65/HEVC [] ae the most common intenational stanas fo still images an vieo compession, espectively. In an image compession base on BDCT, the image egaation woul become visible when the compession atio excees cetain levels. It leas to the iscontinuity of intensities between ajacent blocks ue to the fact that images ae segmente into igi blocks an the coelations between blocks ae neglecte, namely blocking atifacts. In paticula, the BDCT coing images will exhibit sevee blocking atifacts when the bit ates ae vey low. Aitionally, image-blocking atifacts not only become visually annoying, but also have a substantial effect on futhe image pocessing. Theefoe, image eblocking is necessay fo highly compesse images. This is an Open Access aticle istibute une the tems of the Ceative Commons Attibution Non-Commecial License ( which pemits unesticte non-commecial use, istibution, an epouction in any meium, povie the oiginal wok is popely cite. Manuscipt eceive Octobe 8, 015; accepte June 17, 016. Coesponing Autho: Chengyou Wang (wangchengyou@su.eu.cn) * School of Mechanical, Electical an Infomation Engineeing, Shanong Univesity, Weihai, China (suwlp@163.com, zhouxiao@su.eu.cn) ** School of Electonic Infomation, Wuhan Univesity, Wuhan, China ( @qq.com) Copyight 016 KIPS

2 Image Deblocking Scheme fo JPEG Compesse Images Using an Aaptive-Weighte Bilateal Filte In oe to euce the shotcomings of BDCT, many eseaches have popose numeous algoithms. The algoithm that pocesses images only at the ecoe sie is calle a post-pocessing algoithm. A post-pocessing algoithm is moe pactical because it oes not affect the potocol contents of the encoe sie an the potocol oesn t nee to be change. These algoithms mainly inclue spatial filteing [3], tansfom omain filteing [4], pojection iteative metho [5], an so on. To inteact with the outsie wol effectively an apily, the human vision system (HVS) must extact an pocess a lage vaiety of visual infomation fom the captue images. Rathe than aopting a unifom metho to pocess these extacte stuctues fom the captue images, HVS shoul be able to aapt to the iffeent chaactes of these iffeent extacte stuctues. Theefoe, the maximum amount of infomation can be extacte fom the extacte stuctues fo the subsequent ecognition stage an fo image pocessing. It is this point that an aaptive an effective image pocessing system shoul be esigne in oe to make the machines have the aaptive capabilities of biological vision systems. A lot of woks an eseaches have been one fo aaptive image eblocking. Fo suppessing blocking atifacts an peseving image salient featues, Foi et al. [6] popose an aaptive image filteing metho using the shape-aaptive DCT (SA-DCT), which empiical Wiene filteing an ha-thesholing technology wee aopte in the SA-DCT omain. In aition, Zhai et al. [7] popose one kin of a compehensive image-eblocking algoithm, incluing thee pocessing stages. In the secon stages, block-wise shape aaptive filteing was popose to futhe amelioate ege featues. To avoi possible ove-smoothing, a quantization constaint set is also aopte in the thi stage. Futhemoe, the popose metho has elatively low computational complexity. Accoing to the pocess analysis of image coing an the chaacteistics of a BDCT compesse image, we can fomulate image eblocking clealy as optimization poblems that solve the objective function using a set of convex functions [8]. Wang et al. [9] popose an aaptive spatial post-pocessing metho that is compose of thee steps: thesholing, moel classification, an a eblocking filte. Compae with these popose aaptive image-eblocking methos, the most staightfowa way is to conuct low pass filteing aoun the block bounaies. Howeve, low pass filteing filtes out some high fequency infomation, which leas to image ove-smoothing an bluing. To make images obtaine by the optical coheence tomogaphy valuable fo clinical intepetation, Anantasiichai et al. [10] popose an aaptive-weighte bilateal filte. The novel filte not only offes the esiable popety of emoving speckles, but also peseves textue an useful infomation containe in the optical coheence tomogaphy images. Hu et al. [11] esigne one kin of aaptive epth map filte base on a bilateal filte fo image eblocking. The paamete of this popose aaptive epth map filte is change aaptively accoing to image eges an blocking atifacts. In this pape, an oiginal image eblocking metho using an aaptive-weighte bilateal filte is popose. This novel aaptive-weighte bilateal filte is popose base on local entopy an impove blin image quality assessment fo the sake of eliminating blocking atifacts an avoiing ovesmoothing. The est of this pape is oganize as follows: We biefly intouce the elate woks in Section. In Section 3, we pesent the popose aaptive-weighte eblocking filte algoithms. In Section 4, expeimental esults an compaisons ae pesente. Finally, we give ou conclusion an futhe eseach in Section J Inf Pocess Syst, Vol.1, No.4, pp.631~643, Decembe 016

3 Liping Wang, Chengyou Wang, Wei Huang, an Xiao Zhou. Relate Woks.1 Bilateal Filte The bilateal filte [1] is a tool that can smooth images while peseving image eges an textue egions. The pinciple of a bilateal filte is analogous to the Gaussian convolution, which is efine as the weighte aveage of pixel values. The iffeence between a Gaussian filte an bilateal filte is that the bilateal filte takes into account not only the spatial locations but also the intensity vaiation to peseve image eges. The pinciple of bilateal filteing is that two pixels in images ae analogous to each othe base on spatial locations an similaity in the photometic ange. A new weighte aveage of pixel p can be obtaine by Eq. (1): p q S 1 BF[ I p] G p q G I, p Iq I q (1) whee, S is the winow space. G () an G () ae the closeness an the similaity functions that ae the Gaussian functions with the stana eviations of an, espectively. epesents the Eucliean istance, an p is use fo nomalization. The pefomance of a bilateal filte is contolle by two paametes of an. is impotant in image spatial omain pocessing because it etemines the level of low-pass filteing. A geate value of will combine an weigh moe pixels in the neighbohoo togethe, which leas to a geate bluing effect. etemines the weights in an image intensity omain. Accoing to the value of, pixel points in the winow space S whee thei values ae close to each othe ae combine an weighte togethe. Examples of smoothing images by the bilateal filte with fixe paametes ae shown in Fig. 1. The bilateal filte with fixe paametes cannot obtain goo esults in emoving the blocking atifacts. (a) (b) (c) () Fig. 1. Diffeent effects of bilateal filte with fixe paametes: (a) 5, 0.1, (b) 5, 0.3, (c) 0, 0.1, an () 0, 0.3. J Inf Pocess Syst, Vol.1, No.4, pp.631~643, Decembe

4 Image Deblocking Scheme fo JPEG Compesse Images Using an Aaptive-Weighte Bilateal Filte. Local Entopy Accoing to Shannon s efinition of entopy, the image entopy is efine as Eq. (): L1 i0 E Plog P, () i i i whee, i is gayscale an L is the maximal gayscale. P n i epesents the pobability of i in M N the image, n i is the amount of pixel points whose gayscale is i, an the image size is M N. Simila to the image entopy, the local entopy of small neighbohoo within image E( ) can be witten as: k k L1 E( ) P log P, (3) k j j i0 n j whee, j is the gayscale. Pj is the pobability of j in the small neighbohoo k. n j is Mk Nk the amount of pixel points whose gayscale is j in the small neighbohoo k. The winow size of k is M k Nk. Fo the small neighbohoo k, the local entopy E( k ) is closely coelate with the vaiance of gayscales. Fom Eq. (3), the local entopy is smalle in homogeneous egions an lage in inhomogeneous egions. Hence, the pixel points in smooth egions will have smalle local entopy values than those in unsmooth (ege an textue) egions of the image. If we select an appopiate neighbo winow fo the image, the local entopy of the image woul be compute. When the neighbo winow is move on a pe-pixel basis within the image fom top to bottom an fom left to ight, the local entopy value of each pixel point will be obtaine, that is, we can obtain a local entopy image. Fig. is the local entopy map of Lena. Fom Fig., we can see that the ege an textue egions can be clealy istinguishe fom the smooth egions. Fig.. The local entopy map of Lena. 634 J Inf Pocess Syst, Vol.1, No.4, pp.631~643, Decembe 016

5 Liping Wang, Chengyou Wang, Wei Huang, an Xiao Zhou 3. The Popose Scheme Using an Aaptive-Weighte Bilateal Filte To impove the quality of JPEG compesse images, we nee to potect ege an textue infomation when the image is to be eblocke. In othe wos, an must be lage to emove blocking atifacts in smooth egions. Fo egions with moe significant etails, an shoul be smalle to avoi bluing etails. Although a bilateal filte can potect image eges while smoothing the image, the filte with fixe paametes cannot wok well because it may lea to the loss of some textue infomation, as shown in Fig. 1. Local entopy can show the iscete egee of image gayscales. Fo smooth egions of the image, the local entopy is smalle. In textue an ege egions, the local entopy is lage. As such, this pape poposes a novel aaptive-weighte bilateal filte using the local entopy map g( x ) as the guiance image to obtain aaptive paametes. is calculate fo a pixel locate at x : max( n, k ( g g( x) / )), (4) max whee, n is a minimum level of filteing to avoi 0. g max is the maximum value of g( x ), an k is a constant paamete that contols the mapping pocess of g( x ) to. is calculate fo a pixel locate at x : max( n, k ( g g( x) / )), (5) max whee, n is a minimum level of filteing to avoi 0, an k is a constant paamete that contols the mapping pocess of g( x ) to. The paametes k an k ae simila to an which etemine the pefomance of the bilateal filte. The famewok of ou popose aaptiveweighte filte is shown in Fig. 3., Fig. 3. The popose aaptive-weighte bilateal filte fo image eblocking. Fo images whose blocking atifacts ae moe seious, we nee to select lage paametes ( k an k ) to smooth images as much as possible. Fo images with slight blocking atifacts, we shoul select J Inf Pocess Syst, Vol.1, No.4, pp.631~643, Decembe

6 Image Deblocking Scheme fo JPEG Compesse Images Using an Aaptive-Weighte Bilateal Filte smalle paametes ( k an k ) to avoi ove-smoothing images. In this pape, we aopte thee sets of ata fo k an k accoing to the seveity of image blocking atifacts. In geneal, it is not possible to obtain the oiginal image on the ecoe sie. In this pape, we aopte an impove a kin of blin image quality assessment (BIQA) as citeion accoing to [13] to choose appopiate paametes ( k an k ) fo iffeent ecoe images. Fo the test image signal x( mn, ) with m [1, M] an n [1, N], an a iffeencing signal on each hoizontal line can be calculate as: ( m, n) x( m, n1) x( m, n), n[1, N 1]. (6) h Fo a 1-D hoizontal signal fm( n) h( m, n), we fist calculate its powe spectum fo m1,,, M an then aveage them togethe. Finally, the powe spectum estimation Ph (), l 0l / N can be obtaine, which is exemplifie in Fig. 4. As shown in Fig. 4, the iffeent oiginal images have simila powe spectum. When we aopte iffeent quantization factos (Q=1, Q=3, an Q=5), the image blocking atifacts can be easily picke out base on the peaks at the featue fequencies (1/8, /8, 3/8, an 4/8), as shown in Fig. 5. In aition, if the image is compesse moe highly, the peaks will change moe significantly. Accoing to the chaacteistics of the image powe spectum, the citeion to select the paametes ( k an k ) is to calculate S. This is efine as: S 1/8 S1/8 S/8 S3/8 S, (7) 3 PN ( /81) PN ( /81) P( N /8), (8) P( N /81) P( N /81) S/8 P( N / 8), (9) P(3 N /81) P(3 N /81) S3/8 P(3 N / 8). (10) 7 6 Lena Babaa Peppes 5 log(1+p h (l)) l/n Fig. 4. The powe spectum cuves of iffeent images. 636 J Inf Pocess Syst, Vol.1, No.4, pp.631~643, Decembe 016

7 Liping Wang, Chengyou Wang, Wei Huang, an Xiao Zhou oiginal Q = 1 Q = 3 Q = 5 log(1+p h (l)) l/n Fig. 5. The powe spectum cuves of Lena image with iffeent quantization factos. The image quality scoes S of thee images, which ae calculate by Eqs. (7) (10), ae shown in Fig. 6. The thee images ae Lena, Babaa, an Peppes. All of them ae compesse by JPEG whee the quantization facto Q vaies fom 1 to 10. Fom Fig. 6, we can see that if the quality of image is ba, S is lage. The flow iagam of ou popose image-eblocking scheme is shown in Fig. 7. If S was smalle than α, then we selecte ( k, k ) fo ( k, k ) ; if S was lage than an smalle than β, s s then ( k, k ) was use; an if S was lage than β, ( k, k ) was use. The paametes ( k, k ), m m ( k, k ), an ( k, k ) wee etemine empiically an set as follows: ( k, k ) (1,10), m m l ( k, k ) (3,0), an ( k, k ) (5,30). m m l l l l l s s s s Lena Babaa Peppes S Q Fig. 6. The image quality scoes of Lena, Babaa, an Peppes images using quantization facto Q fom 1 to 10. J Inf Pocess Syst, Vol.1, No.4, pp.631~643, Decembe

8 Image Deblocking Scheme fo JPEG Compesse Images Using an Aaptive-Weighte Bilateal Filte S S S k, k k, k k, k s s m m l l Fig. 7. The flow iagam of the popose scheme fo image eblocking. In oe to etemine the theshol values α an β (α<β), we selecte thee images: Lean, Babaa, an Peppes. They wee compesse by JPEG whee the quantization facto Q vaie fom 1 to 10. All of them wee caie out accoing to the steps shown below, which ae also shown in Fig. 8: (i) The fist ecoe image of the Lena (Babaa o Peppes) image is pocesse by the popose aaptive-weighte bilateal filte in which the paametes of ( k, k ) ae ( ks, k s) an ( km, k m), espectively. The obtaine images ae calle output image1 an output image. Thei scoes ae calculate using the popose metho, namely S s an S m. If S s S m, then S 0, which is the quality scoe of the compesse image, is the theshol value α. If Ss Sm, continue to step (ii). This step is shown in the black box an soli line. (ii) The ecoe image is pocesse by the popose aaptive-weighte bilateal filte in which the paametes of ( k, k ) ae ( kl, k l ), an we calculate the scoes of the obtaine image calle output image, namely S l. If Sl Sm, S 0 is the theshol value β. If Sl Sm, S 0 is lage than α an smalle than β. This step is shown in the blue box an otte line. (iii) The othe images of Lena use the same steps to moify α an β. k, k k, k k, k m m s s l l Sm Ss Sl S s Sm Sl Sm S 0 S0 S0 Fig. 8. The flow chat to etemine the theshol values. 638 J Inf Pocess Syst, Vol.1, No.4, pp.631~643, Decembe 016

9 Liping Wang, Chengyou Wang, Wei Huang, an Xiao Zhou In this pape, the best value anges of α an β fo the Lena, Babaa, an Peppes images ae shown in Table 1. Accoing to Table 1, we selecte α= an β= Table 1. The value anges of α an β fo Lena, Babaa, an Peppes images Image α β Lena [0.4766, ] [0.9770, ] Babaa [0.545, ] [0.8903, ] Peppes [0.1710, 0.961] [0.8343, ] 4. Expeimental Results To test the pefomance of ou popose scheme, a lot of expeiments have been conucte on monochome an colo images. In this pape, the images with blocking atifacts wee obtaine by JPEG. Fo monochome images, we use thee igital images Lena, Babaa, an Peppes to test the effectiveness an efficiency of ou popose scheme. Fo colo images, we aopte images fom the LIVE atabase. The metho of bilateal filteing with fixe paametes an the metho popose in [11] wee pefome. These esults wee compae with the esults fom using ou popose algoithm to test the pefomance of ou popose metho. The simulation was conucte with MATLAB 009a. Hee, we compute the PSNR an SSIM between the eblocke image an the uncompesse image. PSNR is efine as shown in Eq. (11): 55 PSNR 10log 10 (B), MSE (11) whee, MSE is the mean squae eo between the eblocke image an the uncompesse image. An SSIM is efine as shown in Eq. (1): ( c )( c ) SSIM( xy, ), ( )( ) x y 1 xy x y c1 x y c (1) whee, x an y ae the aveage of the eblocke image x an the uncompesse image y, espectively, an x an y ae the vaiance of the eblocke image x an the uncompesse image y, espectively. xy is the covaiance of the eblocke image x an the uncompesse image y. c1 ( k1l) an c ( kl) ae the two paametes to pevent the enominato fom being 0. L is the maximal gayscale. In geneal, k an k 0.03 by efault. If SSIM is equal to 0, it means that thee is no coelation between the eblocke image x an the uncompesse image y, an 1 means that the uncompesse image y is almost exactly the same as the eblocke image x. In tems of PSNR an SSIM, Tables 4 show the expeimental esults of ou popose scheme compae to othe methos applie to the Lena, Babaa, an Peppes images at vaious bit ates, espectively. J Inf Pocess Syst, Vol.1, No.4, pp.631~643, Decembe

10 Image Deblocking Scheme fo JPEG Compesse Images Using an Aaptive-Weighte Bilateal Filte Table. Compaisons of iffeent eblocking methos applie to image Lena in tems of PSNR an SSIM PSNR (B) SSIM 0.0 bpp 0.5 bpp 0.30 bpp 0.0 bpp 0.5 bpp 0.30 bpp Compesse Fixe [11] Popose Table 3. Compaisons of iffeent eblocking methos applie to image Babaa in tems of PSNR an SSIM PSNR (B) SSIM 0.7 bpp 0.3 bpp 0.46 bpp 0.7 bpp 0.3 bpp 0.46 bpp Compesse Fixe [11] Popose Table 4. Compaisons of iffeent eblocking methos applie to image Peppes in tems of PSNR an SSIM PSNR (B) SSIM 0.5 bpp 0.30 bpp 0.40 bpp 0.5 bpp 0.30 bpp 0.40 bpp Compesse Fixe [11] Popose Fom Tables 4, we can see that ou popose algoithm has excellent pefomance compae with the two mentione methos. Ou popose scheme can povie the best esults. Fo these images, the esults ae impove fom a minimum of 0.0 B up to 1.00 B in tems of PSNR, an the SSIM is also impove compae with the compesse images. When these images ae at vey low bit ates, the metho popose in [11] an the metho of bilateal filteing with fixe paametes can impove thei quality. Howeve, when the images ae not at vey low bit ates, they cannot impove the quality an may actually euce it. The easons fo this ae that the metho pesente in [11] only changes one paamete an the metho of bilateal filteing with a fixe paamete uses a fixe paamete. Fig. 9 shows the peceive image quality fo the Monach image at a DMOS scoe. Fom Fig. 9, we can see that if we use the bilateal filte with fixe paametes, the image woul be ovesmoothe, as shown in Fig. 9(b). If we only change one paamete of the bilateal filte (metho in [11]), thee is still blackness in the wings fo the Monach image, as shown in Fig. 9(c). Ou metho can achieve bette effects fo image eblocking. 640 J Inf Pocess Syst, Vol.1, No.4, pp.631~643, Decembe 016

11 Liping Wang, Chengyou Wang, Wei Huang, an Xiao Zhou (a) (b) (c) () Fig. 9. Compaison of the subjective quality on Monach: (a) is the compesse image; (b ) ae eblocke images by the bilateal filteing with fixe paametes, metho of [11], an ou popose scheme, espectively. 5. Conclusions A new efficient image blocking scheme base on aaptive-weighte bilateal is popose in this pape. We use a local entopy map as a guiance map to change two paametes ( an ) in a bilateal filte. In this pocess, we also popose one citeion to etemine k an k, because blocking atifacts of iffeent images afte compession ae iffeent. Though these two steps, we wee able to obtain goo esults in tems of PSNR an SSIM. Ou expeimental esults show that the popose scheme can euce the blocking atifacts at low bit ates. In this pape, we i not consie the optimal selection fo the BIQA. Futhemoe, goo impovements can be obtaine by consieing human visual chaacteistics an GPU o the paallel metho. In the futue, we may focus on these issues. Acknowlegement This wok was suppote by the National Natual Science Founation of China (No ), the Natual Science Founation of Shanong Povince, China (No. ZR015PF004), an the pomotive eseach fun fo excellent young an mile-age scientists of Shanong Povince, China (No. BS013DX0). The authos thank Qiming Fu, Yunpeng Zhang, an Heng Zhang fo thei geneous assistance an valuable suggestions. J Inf Pocess Syst, Vol.1, No.4, pp.631~643, Decembe

12 Image Deblocking Scheme fo JPEG Compesse Images Using an Aaptive-Weighte Bilateal Filte Refeences [1] G. K. Wallace, The JPEG still pictue compession stana, IEEE Tansactions on Consume Electonics, vol. 38, no. 1, pp , 199. [] G. J. Sullivan, J. R. Ohm, W. J. Han, an T. Wiegan, Oveview of the high efficiency vieo coing (HEVC) stana, IEEE Tansactions on Cicuits an Systems fo Vieo Technology, vol., no. 1, pp , 01. [3] R. K. Lama, M. R. Choi, J. Y. Pyun, an G. R. Kwon, Post pocessing algoithm fo euction of blocking atifact in HDTV, in Poceeings of the IEEE Intenational Confeence on Consume Electonics, Las Vegas, NV, USA, 014, pp [4] V. Kapinaiah, J. Mukhopahyay, an P. K. Biswas, Image eblocking by tanscoing DCT blocks to wavelet subbans, in Poceeings of the 8th Intenational Symposium on Image an Signal Pocessing an Analysis, Tieste, Italy, 013, pp [5] J. J. Zou an H. Yan, A eblocking metho fo BDCT compesse images base on aaptive pojections, IEEE Tansactions on Cicuits an Systems fo Vieo Technology, vol. 15, no. 3, pp , 005. [6] A. Foi, V. Katkovnik, an K. Egiazaian, Pointwise shape-aaptive DCT fo high-quality enoising an eblocking of gayscale an colo images, IEEE Tansactions on Image Pocessing, vol. 16, no. 5, pp , 007. [7] G. T. Zhai, W. J. Zhang, X. K. Yang, W. S. Lin, an Y. Xu, Efficient eblocking with coefficient egulaization, shape aaptive filteing an quantization constaint, IEEE Tansactions on Multimeia, vol. 10, no. 5, pp , 008. [8] J. Kim an C. B. Sim, Compession atifacts emoval by signal aaptive weighte sum technique, IEEE Tansactions on Consume Electonics, vol. 57, no. 4, pp , 011. [9] J. Wang, Z. S. Wu, G. Jeon, an J. Jeong, An efficient spatial eblocking of images with DCT compession, Digital Signal Pocessing, vol. 4, pp , 015. [10] N. Anantasiichai, L. Nicholson, J. E. Mogan, I. Echova, K. Motlock, R. V. Noth, J. Albon, an A. Achim, Aaptive-weighte bilateal filteing an othe pe-pocessing techniques fo optical coheence tomogaphy, Computeize Meical Imaging an Gaphics, vol. 38, no. 6, pp , 014. [11] W. Hu, O. C. Au, L. Sun, W. X. Sun, L. F. Xu, an Y. J. Li, Aaptive epth map filte fo blocking atifacts emoval an ege peseving, in Poceeings of the IEEE Intenational Symposium on Cicuits an Systems, Seoul, Koea, 01, pp [1] S. Sisuk, Bilateal filteing as a tool fo image smoothing with ege peseving popeties, in Poceeings of the Intenational Electical Engineeing Congess, Chonbui, Thailan, 014, pp [13] Z. Wang, H. Sheikh, an A. C. Bovik, No-efeence peceptual quality assessment of JPEG compesse images, in Poceeings of the IEEE Intenational Confeence on Image Pocessing, Rocheste, NY, USA, 00, pp Liping Wang She was bon in Shanong povince, China, in She eceive he B.E. egee in communication engineeing fom Shanong Univesity, Weihai, China, in 014. She is cuently pusuing he M.E. egee in signal an infomation pocessing at Shanong Univesity, China. He cuent eseach inteests inclue igital image pocessing an compute vision. 64 J Inf Pocess Syst, Vol.1, No.4, pp.631~643, Decembe 016

13 Liping Wang, Chengyou Wang, Wei Huang, an Xiao Zhou Chengyou Wang He was bon in Shanong povince, China, in He eceive his B.E. egee in electonic infomation science an technology fom Yantai Univesity, China, in 004, an his M.E. an Ph.D. egees in signal an infomation pocessing fom Tianjin Univesity, China, in 007 an 010, espectively. He is cuently an associate pofesso an supeviso of postgauate stuents at Shanong Univesity, Weihai, China. His cuent eseach inteests inclue igital image/vieo pocessing an analysis (tansfom coing, igital watemaking, image ehazing, image quality assessment, etc.), compute vision (tampe etection, image etieval, etc.), an patten ecognition an machine leaning. Wei Huang He was bon in Inne Mongolia autonomous egion, China, in He eceive his B.E. egee in electonic infomation science an technology fom Wuhan Univesity, China, in 014. He is cuently pusuing his M.E. egee in communication an infomation system at Wuhan Univesity, China. His cuent eseach inteests inclue wieless communication technology an igital image pocessing. Xiao Zhou She was bon in Shanong povince, China, in 198. She eceive he B.E. egee in automation fom Nanjing Univesity of Posts an Telecommunications, China, in 003; he M.E. egee in infomation an communication engineeing fom Inha Univesity, Koea, in 005; an he Ph.D. egee in infomation an communication engineeing fom Tsinghua Univesity, China, in 013. She is cuently a lectue an supeviso of postgauate stuents at Shanong Univesity, Weihai, China. He cuent eseach inteests inclue wieless communication technology, igital image pocessing, an compute vision. J Inf Pocess Syst, Vol.1, No.4, pp.631~643, Decembe