Still Image Conpression JPEG & JPEG2000 Yu-Wei Chang /18

Outline Image Compression Background Overview of JPEG Overview of JPEG2000 Comparsion

Why Image Conpression Why? Bandwidth Storage How Remove redundancy

Still Image Coding Flow Most still image coding flow are similar Transform: translate image to freq domain Quantization: reduce unimportant data Entropy coding: encode data according to probability of coeff TransformQuantization Entropy Coding Image data Output data equal important High-> low ……

JPEG

Joint Photographic Expert Group A generally used lossy image coding format Allow tradeoff between compression ratio and image quality Can achieve high compression ratio(20+) with almost invisible difference

JPEG Coding/Decoding Flow DCTQuantizerDataEntropy Coder Coding Table Quantization Table Tables Data Tables Entropy Decoder Inverse Quantizer IDCT Coding Table Quantization Table

JPEG-2000

JPEG 2000 Features Not only better efficiency, but also more functionality Superior low bit-rate performance Lossless and lossy compression Multiple resolution Range of interest(ROI)

JPEG2000 v.s. JPEG low bit-rate performance

JPEG2K - Quality Scalability Improve decoding quality as receiving more bits:

Spatial Scalability Multi-resolution decoding from one bit- stream:

ROI (range of interest)

JPEG2000 Encoder Block Diagram Key Technologies: Discrete Wavelet Transform (DWT) Embedded Block Coding with Optimized Truncation (EBCOT) transformquantize coding

Discrete Wavelet Transform LL 2 HL 2 LH 2 HH 2 HL 1 LH 1 HH 1

JPEG v.s. JPEG-2000

JPEG2000 v.s. JPEG TransformQuantization Entropy Coding JPEG J2K DCT Discrete Cosine Transform DWT Discrete Wavelet Transform 8x8 Quantization Table Quantization for each sub-band Huffman Coding Arithmetic Coding

Conclusion JPEG2000 provides more functionality, and higher compression performance at low bit-rate However, higher complexity, and more memory requirement.