Image, video and audio coding concepts. Roadmap. Rationale. Stefan Alfredsson. (based on material by Johan Garcia)

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1 Image, video and audio coding concepts Stefan Alfredsson (based on material by Johan Garcia) Roadmap XML Data structuring Loss-less compression (huffman, LZ77,...) Lossy compression Rationale Compression is about removing redundant information, and decompression is about restoring to the original state For loss-less compresson, decompressed data is identical to compressed data But, higher compression can be achieved by allowing a quality tradeoff! For example: removing all wovels from a text Fr xmpl: rmvng ll wvl frm txt Obviously not suitable for all kinds of data But image/video/audio are good candidates 1

2 The case for image compression The human is impatient and half blind Impatient Frustrated by waiting behind the screen (i.e. need compression for faster transfer) Half blind The human vision does not catch all information The seeing sense Color vision worse than BW Limited resolution Different sensitivity to different patterns Sharp contrast hides weaker (image from ) Compression example Original Compressed 73 kbyte 11 kbyte > 6 times faster download! 2

3 What s differing? Compression Common Image Formats GIF (Graphis Interchange Format) Lossless, but only in 256 colors Uses LZW for compression (Patent problem) PNG (Portable Network Graphics) More flexible replacement for GIF JPEG (Joint Photographers Expert Group) Complex standard with many modes Typically lossy, but has lossless mode as well JPEG The best compression for photo-like natural images Color or grayscale images Lossy or lossless compression Sequential or progressive display Exploits human visual system characteristics 3

4 JPEG functional overview Color conversion and downsample Split in 8x8 pixel blocks Do DCT (Discrete Cosine Transformation) Quantize Difference encode DC and runlength encode AC Huffman encode Packetize Color conversion, color split RGB pixel image =>JPEG Image normally represented in RGB format (8 bits per color channel per pixel indicate pixel colors) Color split: RGB is converted into Y Cb Cr color format Y Luminance Cb Chrominance (blue) Cr Chrominance (red) Split into three components (Y Cb Cr Color format) Color downsampling RGB pixel image =>JPEG Color split and downsample The eye less sensitive to chrominance (color details) than to luminance (brightness details) ==> Downsample color components Downsampling the chroma components saves 33% or 50% of the space taken by the image. Downsample chrominance components 4

5 Splitting into blocks RGB pixel image =>JPEG Color split and downsample Split in blocks Split into 8x8 pixel blocks DCT transform RGB pixel image =>JPEG Color split and downsample Split in blocks and do DCT DCT indicates the amount of intensity variation (spatial frequency) Perform DCT Why DCT? Spatial locality! 5

6 An 8x8 pixel block is transformed into 64 spatial frequencies (coefficients) Sort of 2-dimensional fourier transform Image Frequencies Summing of coefficients By using all 64 coefficients a perfect reconstrucion is possible Using fewer coefficients gives a good reconstruction and data reduction Ursprungsbild Quantization / = The quantization reduces the resolution (i.e. The amount of information) for the coefficents The number of zero coefficients is increased 6

7 Encoding DCT - DC RGB pixel image =>JPEG Color split and downsample Split in blocks and do DCT Quantize Diff code DC Differential encode DC coefficient Encoding DCT - AC RGB pixel image =>JPEG Color split and downsample Split in blocks and do DCT Quantize Diff code DC and RLE AC Run Length Encode AC coefficients The quantized coefficents are coded in a zig-zag manner This leads to longer zero runlength for the last coefficients. Zig-zag order 7

8 Packetization RGB pixel image =>JPEG Color split and downsample Split in blocks and do DCT Quantize Diff code DC and RLE AC Huffman encode Packetize Headers One Minmum Coded Unit Coder - overview Decoder - overview 8

9 Image format recommendations Photo-like images JPEG Photo or drawn images PNG or GIF These use lossless compression Text PNG or GIF High contrast, will be blurred by jpeg Trim JPEG quality Avoid browser scaling Adjust filesize before to reduce download speed Easy to upload 5 Mpix image, but image to be displayed in 800x600 (0.48 Mpix) album!) Size/quality comparisons (Från: Video coding 9

10 Video Coding Video coding MPEG1, originally for 1x CD-spelare ( vcd ) MPEG2, Digital Satellite och cable-tv Used for example in DVB-T for Boxer marksänd digitaltv Video coding for conferencing H.261, older standard, used with e.g. ISDN H.263, newer standard. Works better at low transmission speeds. Netmeeting Used for most Flash videos (YouTube, Google Video, Myspace, and others) Basis of RealVideo / RealPlayer until RealVideo 8 New technology MPEG 4 (a subset of MPEG4 is used in DivX, XviD, H.264, and other codecs) Overview video coding Video coding concepts Spatial Redundancy Nearby pixels typically have similar values Removed by DCT-transform/quantization/huffman encoding (like in JPEG) Temporal Redundancy Video frames in sequence typically have similar content Removed by macro block coding with motion vectors and difference frames 10

11 Macro block coding The motion vector specify how much and at which way the macro block has moved. The difference frame specify the difference within the macro block between frames. Macro block coding 2 I, P and B frames 11

12 Transmission order MPEG 4 Mpeg 4 är object based, where both image and audio objects may be placed in a 3D coordinate system. These objetcs can then be coded and manipulted independently of each other. The viewer may also interact with the settning, change viewing angles, and so on. Mesh coding An area in the picture can be modeled with a mesh. The mesh parameters are then changed when the area is changed. The texture is rescaled according to the mesh changes. Wireline models of face and animation of wirelinefaces with mapped textures are specified in MPEG 4 ver 1. Later versions have included models of human body and corresponding motion patterns. 12

13 Sprite coding A picture can be composed with a fixed background and a moving sprite. The background can be larger than what is shown on screen, to facilitate camera panorama without transmitting a new background. (compare to weather forecasts on TV, where the background is really blue and the background / weather map / is added afterwards) Audio coding Audio coding Use redundancy in data Similarities in channels in stereo sound Use the weaknesses of the hearing sense (psycho acoustics) Hearing thresholds Frequency bound masking Time bound masking 13

14 Hearing threshold The hearing sensitivity varies for different frequencies What can not be detected does not need tranmission Frequency masking A strong tone masks (conceals/hides) nearby tones The mask width varies with the frequency. Higher = broader Time masking Strong tones also mask in time We can not sense nearby tones right after a strong tone has finished 14

15 Masking Frequency and time masking can be modeled as a surface Tones below the surface can not be sensed, and their information does not need coding / transmission MPEG 2 - Audio Layer 3 (MP3) Algorithm: 1. Separate the audio into 32 subbands with a filter 2. Compute the mask that every band cause 3. If the audio strength in one subband is masked, do not code that subband 4. Determine quantization with regard to masking and bit rate 5. Huffman encode 6. Format output stream Q? 15

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