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An Effective Method to Treat The Boundary Pixels for Image Compression with DWT  

서영호 (광운대학교 전자재료공학과 Digital Design & Test 연구실)
김종현 (광운대학교 전자재료공학과 Digital Design & Test 연구실)
김대경 (한양대학교 응용수학과)
유지상 (광운대학교 전자공학과)
김동욱 (광운대학교 전자재료공학과 Digital Design & Test 연구실)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.27, no.6A, 2002 , pp. 618-627 More about this Journal
Abstract
In processing images using 2 dimensional Discrete Wavelet Transform(2D-DWT), the method to process the pixels around the image boundary may affect the quality of image and the cost to implement in hardware and software. This paper proposed an effective method to treat the boundary pixels, which is apt to implement in hardware and software without losing the quality of the image costly. This method processes the 2-D image as 1-D array so that 2-D DWT is performed by considering the image with the serial-sequential data structure (Serial-Sequential Processing). To show the performance and easiness in implementation of the proposed method, an image compression codec which compresses image and reconstructs it has been implemented and experimented. It included log-scale fried quantizer, but the entropy coder was not implemented. From the experimental results, the proposed method showed the SNR of almost the same SNR(Signal to Noise Ratio) to the Periodic Expansion(PE) method when the compression ratio(excluding entropy coding) of 2:1, 15.3% higher than Symmetric Expansion(SE) method, and 9.3% higher than 0-pixel Padding Expansion(ZPE) method. Also PE method needed 12.99% more memory space than the proposed method. By considering only the compression process, SE and ZPE methods needed additional operations than the proposed one. In hardware implementation, the proposed method in this paper had 5.92% of overall circuit as the control circuit, while SE, PE, and ZPE method has 22%, 21,2%, and 11.9% as the control circuit, respectively. Consequently, the proposed method can be thought more effective in implementing software and hardware without losing any image quality in the usual image processing applications.
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