a new dynamic finite-state vector quantization algorithm for image compression jyi-chang tsai,...
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![Page 1: A New Dynamic Finite-State Vector Quantization Algorithm for Image Compression Jyi-Chang Tsai, Chaur-Heh Hsieh, and Te-Cheng Hsu IEEE TRANSACTIONS ON IMAGE](https://reader035.vdocument.in/reader035/viewer/2022062313/56649d575503460f94a356d9/html5/thumbnails/1.jpg)
A New Dynamic Finite-State Vector Quantization
Algorithm for Image Compression
Jyi-Chang Tsai, Chaur-Heh Hsieh, and Te-Cheng Hsu
IEEE TRANSACTIONS ON IMAGE PROCESSINIG , NOVEMBER 2000
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VQ for image coding
• VQ which exploits the correlation among neighboring blocks– Predictive VQ– Finite-state VQ (FSVQ)– Dynamic FSVQ– Address VQ– Index search VQ
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Vector Quantization (VQ)
X1
X2
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DFSVQ
![Page 5: A New Dynamic Finite-State Vector Quantization Algorithm for Image Compression Jyi-Chang Tsai, Chaur-Heh Hsieh, and Te-Cheng Hsu IEEE TRANSACTIONS ON IMAGE](https://reader035.vdocument.in/reader035/viewer/2022062313/56649d575503460f94a356d9/html5/thumbnails/5.jpg)
Proposed DFSVQ
• Search the best block in predefined search area which contains previously encoded data.
• The current input block can be represented by the best block, dynamic codebook or super-codebook.
• The search for the the best block from the the search area is equivalent to expanding the code-vector space. Thus the picture is superior to the basic VQ with full search method.
![Page 6: A New Dynamic Finite-State Vector Quantization Algorithm for Image Compression Jyi-Chang Tsai, Chaur-Heh Hsieh, and Te-Cheng Hsu IEEE TRANSACTIONS ON IMAGE](https://reader035.vdocument.in/reader035/viewer/2022062313/56649d575503460f94a356d9/html5/thumbnails/6.jpg)
Proposed DFSVQ (cont.)
![Page 7: A New Dynamic Finite-State Vector Quantization Algorithm for Image Compression Jyi-Chang Tsai, Chaur-Heh Hsieh, and Te-Cheng Hsu IEEE TRANSACTIONS ON IMAGE](https://reader035.vdocument.in/reader035/viewer/2022062313/56649d575503460f94a356d9/html5/thumbnails/7.jpg)
![Page 8: A New Dynamic Finite-State Vector Quantization Algorithm for Image Compression Jyi-Chang Tsai, Chaur-Heh Hsieh, and Te-Cheng Hsu IEEE TRANSACTIONS ON IMAGE](https://reader035.vdocument.in/reader035/viewer/2022062313/56649d575503460f94a356d9/html5/thumbnails/8.jpg)
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![Page 10: A New Dynamic Finite-State Vector Quantization Algorithm for Image Compression Jyi-Chang Tsai, Chaur-Heh Hsieh, and Te-Cheng Hsu IEEE TRANSACTIONS ON IMAGE](https://reader035.vdocument.in/reader035/viewer/2022062313/56649d575503460f94a356d9/html5/thumbnails/10.jpg)
Simulation Results
![Page 11: A New Dynamic Finite-State Vector Quantization Algorithm for Image Compression Jyi-Chang Tsai, Chaur-Heh Hsieh, and Te-Cheng Hsu IEEE TRANSACTIONS ON IMAGE](https://reader035.vdocument.in/reader035/viewer/2022062313/56649d575503460f94a356d9/html5/thumbnails/11.jpg)
![Page 12: A New Dynamic Finite-State Vector Quantization Algorithm for Image Compression Jyi-Chang Tsai, Chaur-Heh Hsieh, and Te-Cheng Hsu IEEE TRANSACTIONS ON IMAGE](https://reader035.vdocument.in/reader035/viewer/2022062313/56649d575503460f94a356d9/html5/thumbnails/12.jpg)
![Page 13: A New Dynamic Finite-State Vector Quantization Algorithm for Image Compression Jyi-Chang Tsai, Chaur-Heh Hsieh, and Te-Cheng Hsu IEEE TRANSACTIONS ON IMAGE](https://reader035.vdocument.in/reader035/viewer/2022062313/56649d575503460f94a356d9/html5/thumbnails/13.jpg)
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VQ
0.563 bpp,
31.10 dB
DFSVQ-N
(0.430 bpp. 31.06 dB),
Original
![Page 15: A New Dynamic Finite-State Vector Quantization Algorithm for Image Compression Jyi-Chang Tsai, Chaur-Heh Hsieh, and Te-Cheng Hsu IEEE TRANSACTIONS ON IMAGE](https://reader035.vdocument.in/reader035/viewer/2022062313/56649d575503460f94a356d9/html5/thumbnails/15.jpg)
SMVQ
(0.412 bpp, 31.10 dB),
PDFSVQ
0.246 bpp, 31.07 dB
![Page 16: A New Dynamic Finite-State Vector Quantization Algorithm for Image Compression Jyi-Chang Tsai, Chaur-Heh Hsieh, and Te-Cheng Hsu IEEE TRANSACTIONS ON IMAGE](https://reader035.vdocument.in/reader035/viewer/2022062313/56649d575503460f94a356d9/html5/thumbnails/16.jpg)
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Conclusions
• For each input block, the PDFSVQ first searches the best block. Then, the current block is encoded by the best block, dynamic codebook or super-codebook, depending on the coding distortion.
• The PDFSVQ exploits the global correlation of image blocks rather than local correlation in conventional memory VQs.
![Page 18: A New Dynamic Finite-State Vector Quantization Algorithm for Image Compression Jyi-Chang Tsai, Chaur-Heh Hsieh, and Te-Cheng Hsu IEEE TRANSACTIONS ON IMAGE](https://reader035.vdocument.in/reader035/viewer/2022062313/56649d575503460f94a356d9/html5/thumbnails/18.jpg)
Conclusions (cont.)
• The PDFSVQ expands the codebook space without extra overhead information bits; thus, it achieves better rate-dis-tortion performance and visual quality than conventional DFSVQs.