Presentation on theme: "JPEG DCT Quantization FDCT of 8x8 blocks."— Presentation transcript:
1JPEG DCT Quantization FDCT of 8x8 blocks. Order in increasing spatial frequency (zigzag)Low frequencies have more shape information, get finer quantization.High’s often very small so go to zero after quantizingIf source has 8-bit entries ( s in [-27, 27-1), can show that quantized DCT needs at most 11 bits (c in [-210, 210-1])See Wallace paper, p 12.Note high frequency contributions small.
2JPEG DCT Quantization Quantize with single 64x64 table of divisors Quantization table can be in file or reference to standardStandard quantizer based on JND.Note can have one quantizer table for each image componentSee Wallace p 12.
3JPEG DCT Intermediate Entropy Coding Variable length code (Huffman):High occurrence symbols coded with fewer bitsIntermediate code: symbol pairssymbol-1 chosen from table of symbols si,ji is run length of zeros preceding quantized dct amplitude,j is length of huffman coding of the dct amplitudei = 0…15, j= 1…10, and s0,0=‘EOB’ s15,0 = ‘ZRL’symbol-2: Huffman encoding of dct amplitudeFinally, these 162 symbols are Huffman encoded.
4JPEG componentsY = 0.299R G B Cb = R G + 0.5B Cr = 0.5R G BOptionally subsample Cb, Crreplace each pixel pair with its average. Not much loss of fidelity. Reduce data by 1/2*1/3+1/2*1/3 = 1/3More shape info in achromatic than chromatic components. (Color vision poor at localization).
5JPEG goodiesProgressive mode - multiple scans, e.g. increasing spatial frequency so decoding gives shapes then detailHierarchical encoding - multiple resolutionsLossless coding modeJFIF:User embedded datamore than 3 components possible?