A COMPRESSION TECHNIQUES IN DIGITAL IMAGE PROCESSING - REVIEW

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1 A COMPRESSION TECHNIQUES IN DIGITAL IMAGE PROCESSING - ABSTRACT: REVIEW M.JEYAPRATHA 1, B.POORNA VENNILA 2 Department of Computer Application, Nadar Saraswathi College of Arts and Science, Theni, Tamil Nadu. In image compression can reduce the quantities of pixels used in image representation without excessively change image visualization. Reducing image size can enhance image sharing, transmitting image and storing. There are two types of compressions available namely lossy and lossless. This paper deals with lossy compression techniques named Fractal, Wavelet, JPEG and advantages and disadvantages and its applications. And lossless compression techniques named Run length coding, Huffman coding, Arithmetic coding and advantages and disadvantages and its applications. [1] INTRODUCTION A digital image is a numeric representation, normally binary of a two-dimensional image. Depending on whether the image resolution is fixed, it may be of vector or raster type. By itself, the term DIGITAL IMAGE usually refers to raster image or bitmapped image. Digital image processing (DIP) is the technique of manipulating these group of bits (pixel) to enhance the quality of the image or create different perspectives or to extract information from the image digitally, with the help of computer algorithms. [2] TYPES OF IMAGE COMPRESSION There are two types of image compression techniques are available. Lossy compression Lossless compression

2 A COMPRESSION TECHNIQUES IN DIGITAL IMAGE PROCESSING - REVIEW [2.1] LOSSY COMPRESSION Lossy compression method is one where compressing data and then decompressing it retrieves data that will be different from the original, but it close enough to be useful. In some way, Lossy compression is most commonly used to compress multimedia data (Audio, Video, Still images especially in applications, such as streaming media and internet telephony. On the other hand Lossless compression is preferred for text and data files. Such as bank records, text articles etc., TECHNIQUES The lossy compression techniques are Fractal compression Wavelet compression JPEG compression Compression EXAMPLE FOR LOSSY COMPRESSION [2.2] LOSSLES COMPRESSION It is a class of data compression algorithms that s allows the original data to be perfectly reconstructed from the compressed data. If,in a compression process, original data can be

3 recovered without any loss after decompressing the compressed data, it is called a lossless compression, which is generally used for compressing discrete data. TECHNIQUES The lossless compression techniques are Run Length encoding Huffman coding Arithmetic coding Compressed EXAMPLE FOR LOSSLESS COMPRESSION [2.1] LOSSY COMPRESSION ALGORITHM [2.1.1] FRACTAL COMPRESSION The basic thing behind this coding is to divide image into segments by using standard points like color difference, edges, frequency & texture. It is obvious that parts of an image &

4 A COMPRESSION TECHNIQUES IN DIGITAL IMAGE PROCESSING - REVIEW other parts of the same image are usually resembling. Here, there is a dictionary which is used as a look up table called as fractal segments. The library contains codes which are compact sets of number. Doing an algorithm operation, fractals are operated and image is encoded. This scheme is far more effective for compressing images that are natural & textured. [2.1.2] WAVELET COMPRESSION Wavelets compression is very popular compression approach in mathematics & digital image processing area because of their ability to effective represent &analysis of data. Image compression algorithms based on Discrete Wavelet Transform (DWT), such as Embedded Zero Wavelet (EZW) which capable of excellent compression performance, both in terms of statistical Peak Signal to Noise Ratio (PSNR) & subjective human perception of the reconstructed image. [2.1.3] JPEG COMPRESSION JPEG which stands for Joint Photographic Experts Group is a lossy compression algorithm for images.jpeg images look almost the same as the original images they were derived from most of the time, unless the quality is reduced significantly, in which case there will be visible difference. [2.1.4] ADVANTAGES AND DISADVANTAGES OF FRACTAL, WAVELET, AND JPEG COMPRESSION Method Advantages Disadvantages Fractal a.) Good mathematical encoding frame. b.) Resolution free decoding. a.) Slow encoding.

5 Wavelet a.) High compression ratio. b.) Low encoding complexity. c.) It produces no blocking artifacts. JPEG a.) Current standard. b.) High quality. c.) Comparatively fast with other methods. a.) Coefficient quantization. b.) Less efficient. a.) Coefficient quantization. b.) Bit allocation. [2.2] LOSSLESS COMPRESSION ALGORITHM [2.2.1] RUN LENGTH ENCODING Run Length Encoding (RLE) is an entropy encoding compression technique that works on inter pixel redundancy. The compression proceeds by first, finding the run of data in the image. Run of data refers to sequences in which same value occurs in many consecutive elements. When such runs of data are identified, they are stored as a set of two values-one value being the original value that composes the run and the number of times the value is repeated. This compression algorithm is suitable for line drawing logs and small animation files. [2.2.2] HUFFMAN CODING Huffman coding is one of the basic compression methods, that have proven useful in image and video compression standards. When applying on an image, the source symbols can be either pixel intensities of the image, or the output of an intensity mapping function. [2.2.3] ARITHMETIC CODING Arithmetic Coding is a common algorithm used in both lossless and lossy data compression algorithms. It is an entropy encoding techiue, in which the frequently seen symbols

6 A COMPRESSION TECHNIQUES IN DIGITAL IMAGE PROCESSING - REVIEW are encoded with fewer bits than rarely seen symbols. Arithmetic Coding has better performance than Huffman Coding. [3] APPLICATION OF DIGITAL IMAGE PROCESSION: Some of the major fields in which are using digital image processing : Image sharpening and restoration. Medical field. Remote sensing. Transmission and encoding. Machine / robot vision. Color processing. Pattern recognition. Video processing. Microscopic imaging. [4] CONCLUSION This paper points out different basic image compression techniques. As there are two types of compression techniques namely lossy and lossless. Lossy compression technique produce a loss of information at the cost of reduction in size. And the other technique lossless compression technique do not produce any loss of information. But the lossy compression have certain limitations which losing a slight information from an image in some fields like medical. [5] REFERENCES [1] Khobragade P. B., Image Compression Techniques - a Review, et al, (IJCSIT) International Journal of Computer Science and Information Technologies, ISSN: , Vol. 5 (1), 2014, [2] Mr. Chandresh K Parmar, Prof.Kruti Pancholi, A Review on Image Compression Techniques Journal of Information, Knowledge And Research in Electrical Engineering ISSN: volume 02, Issue 02 Nov 12 to Oct 13. [3] R. Navaneethakrishnan, Study of Image Compression Techniques International Journal of Scientific & Engineering Research, Volume 3, Issue 7, July

7 [4] Vikas Singla, Rakesh Singla and Sandeep Gupta, Data compression modelling:huffman and Arithmetic, International Journal of The Computer, the Internet and Management, Vol. 16 No.3, Page(s):64-68.Sept - Dec, [5] O.Srinivasa Rao, Prof.S.Pallam Setty, Comparative Study of Arithmetic and Huffman Compression Techniques for Enhancing Security and Effective Bandwidth Utilization in the Context of ECC for Text, International Journal of Computer Applications, Vol. 29 No.6, Page(s):44-60, September [6] Sonal Dinesh Kumar, A Study of Various Image CompressionTechniques, Proceedings of COIT, RIMT Institute of Engineering and Technology, Pacific, 2000, pp