DIGITAL IMAGE DIGITAL IMAGE COMPRESSION COMPRESSION Fernando Pereira Fernando Pereira Instituto Superior Técnico Instituto Superior Técnico Audiovisual Communications, Fernando Pereira, 2012
Multilevel Photographic Image Coding Multilevel Photographic Image Coding Multilevel Photographic Image Coding Multilevel Photographic Image Coding (gray and colour) (gray and colour) (gray and colour) (gray and colour) OBJECTIVE OBJECTIVE Efficient representation of multilevel photographic images Efficient representation of multilevel photographic images (still pictures) for storage and transmission. (still pictures) for storage and transmission. Audiovisual Communications, Fernando Pereira, 2012
Applications Applications Applications Applications � Digital cameras � Image databases, e.g. museums, maps � Desktop publishing � Colour fax � Medical images � ... � and Digital cinema (!) Audiovisual Communications, Fernando Pereira, 2012
The Image Representation Problem ... The Image Representation Problem ... The Image Representation Problem ... The Image Representation Problem ... A image is created and consumed as a set of M × × N luminance and chrominance × × samples with a certain number of bits per sample (P). Thus, the total number of bits (M × × N × × P) × × × × - and so the memory and bandwidth – necessary to PCM digitally represent an image is HUGE !!! Audiovisual Communications, Fernando Pereira, 2012
Image (Source) Coding Objective Image (Source) Coding Objective Image (Source) Coding Objective Image (Source) Coding Objective Image coding/compression deals with the efficient representation of images, satisfying the relevant requirements. And these requirements keep changing, e.g., coding efficiency, error resilience, random access, interaction, editing, to address new applications and functionalities ... Audiovisual Communications, Fernando Pereira, 2012
Where does Compression come from ? Where does Compression come from ? Where does Compression come from ? Where does Compression come from ? � � REDUNDANCY REDUNDANCY – Regards the similarities, correlation and predictability of samples and symbols corresponding to the image/audio/video data. -> redundancy reduction does not involve any information loss, implying it is a reversible process –> lossless coding � � IRRELEVANCY IRRELEVANCY – Regards the part of the information which is imperceptible for the visual or auditory human systems. -> irrelevancy reduction involves removing non-redundant information, implying it is an irreversible process -> lossy coding Source coding exploits these two concepts: for this, it is necessary to know the source statistics and the human visual/auditory systems characteristics. Audiovisual Communications, Fernando Pereira, 2012
Imagem Imagem Coding: Multiple Technical Solutions Imagem Imagem Coding: Multiple Technical Solutions Coding: Multiple Technical Solutions Coding: Multiple Technical Solutions � DCT-based transform coding, e.g. JPEG standard � Fractal-based coding � Vector quantization coding � Wavelet-based coding, e.g. JPEG 2000 standard � Lapped biorthogonal-based transform coding, e.g. JPEG XR standard � … Audiovisual Communications, Fernando Pereira, 2012
The The JPEG Standard JPEG Standard (Joint Photographic Experts Group, joint ISO & ITU (Joint Photographic Experts Group, joint ISO & ITU-T) T) Audiovisual Communications, Fernando Pereira, 2012
Objective Objective Objective Objective Definition of a generic compression standard for multilevel Definition of a generic compression standard for multilevel photographic images considering the requirements of most photographic images considering the requirements of most applications. applications. Audiovisual Communications, Fernando Pereira, 2012
Interoperability, thus Standards ! Interoperability, thus Standards ! Interoperability, thus Standards ! Interoperability, thus Standards ! � Image coding is used in the context of many applications where interoperability is an essential requirement. � The interoperability requirement is satisfied through the specification of a coding standard which represents a voluntary agreement between multiple parties. � To foster evolution and competition, standards must offer interoperability through the specification of the smallest number of tools. Audiovisual Communications, Fernando Pereira, 2012
The The The The Importance of Importance of Importance of Importance of Good Good Good Good Requirements Requirements Requirements Requirements … … Audiovisual Communications, Fernando Pereira, 2012
JPEG Standard Major Requirements JPEG Standard Major Requirements JPEG Standard Major Requirements JPEG Standard Major Requirements ≈ 1985 � � Efficiency Efficiency - The standard must be based on the most efficient compression techniques, notably for very high quality. � � Compression/Quality Tunable Compression/Quality Tunable - The standard shall allow tuning the quality versus compression efficiency. � Generic � Generic - The standard must be applicable to any type of multilevel photographic images without restrictions in resolution, aspect ratio, color space, content, etc. � � Low Complexity Low Complexity - The standard must be implementable with a reasonable complexity; notably, its software implementation on a large range of CPUs must be possible. � � Functional Flexibility Functional Flexibility - The standard must provide various relevant operation modes, notably sequential, progressive, lossless and hierarchical. Audiovisual Communications, Fernando Pereira, 2012
JPEG Elements JPEG JPEG Elements JPEG Elements Elements Encoder Coded bitstream v Tables Original image Decoder Coded bitstream v Tables Decoded image Audiovisual Communications, Fernando Pereira, 2012
What Images can JPEG Encode ? What Images can JPEG Encode ? What Images can JPEG Encode ? What Images can JPEG Encode ? � Size between 1×1 and 65535×65535 � 1 to 255 colour components or spectral bands (typically YC R C B or RGB) � Each component, C i , consists of a matrix with x i columns and y i lines � 8 or 12 bits per sample for DCT based compression � 2 to 16 bits per sample for lossless compression Audiovisual Communications, Fernando Pereira, 2012
ITU ITU-R 601 Recommendation: a Typical ITU-R 601 Recommendation: a Typical ITU R 601 Recommendation: a Typical R 601 Recommendation: a Typical Resolution Resolution Resolution Resolution � Most important standard PCM video/image format � Basic sampling rate: 13.5 MHz for the luminance and 6.75 MHz for the chrominances � Considers 625 and 525 lines systems for 25 and 30 Hz systems, respectively (576 and 480 useful lines for 25 and 30 Hz) � Considers both 4:3 and 16:9 aspect ratios � Quantization: 8 bit/sample Audiovisual Communications, Fernando Pereira, 2012
Colour Subsampling Formats Colour Subsampling Formats Colour Subsampling Formats Colour Subsampling Formats Format Resolution Y ResolutionU/V Horizontal Vertical 4:4:4 720 x 576 720 x 576 1:1 1:1 4:2:2 720 x 576 360 x 576 2:1 1:1 4:2:0 720 x 576 360 x 288 2:1 2:1 4:1:1 720 x 576 180 x 576 4:1 1:1 4:1:0 720 x 576 180 x 144 4:1 4:1 Audiovisual Communications, Fernando Pereira, 2012
The Explanation … The Explanation … The Explanation … The Explanation … • The chroma sub-sampling is generally expressed as a three part ratio J : A : B, describing the number of luma and chrominance samples in a determined area. • This area has J pixels wide and 2 pixels high, being referred to as conceptual area . The value of A defines the number of chrominance samples, CB and CR, in the first row, while B is the number of chrominance samples in the second row of the conceptual area. Audiovisual Communications, Fernando Pereira, 2012
4:2:0 Different 4:2:0 Different Flavours 4:2:0 Different 4:2:0 Different Flavours Flavours … Flavours … … … Audiovisual Communications, Fernando Pereira, 2012
Types Types of Types Types of of JPEG of JPEG JPEG Compression JPEG Compression Compression Compression � LOSSLESS � LOSSLESS - The image is reconstructed with no losses, this means it is mathematically equal to the original; compression factors of about 2-3 may be achieved depending on the image content. � � LOSSY LOSSY – The image is reconstructed with losses but with a very high fidelity to the original, if desired (transparent coding); this type of coding allows to achieve higher compression factors, e.g. 10, 20 or more; in the JPEG standard, this type of coding is based on the Discrete Cosine Transform (DCT). Audiovisual Communications, Fernando Pereira, 2012
JPEG JPEG Baseline Baseline Process Process The most used JPEG coding solution is DCT based (lossy), called BASELINE SEQUENTIAL PROCESS and it is adequate to inumerous applications. This process is mandatory for all systems claiming JPEG compliance. Audiovisual Communications, Fernando Pereira, 2012
DCT Based Image Coding DCT Based Image Coding DCT Based Image Coding DCT Based Image Coding Statistical Redundancy Spatial Quantization Redundancy Coding tables tables Block Entropy DCT Quantization splitting coder ≠ Transmission or storage Irrelevancy Quantization Coding tables tables Inverse Entropy Block IDCT quantization decoder assembling Audiovisual Communications, Fernando Pereira, 2012
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