JPEG2000 정지영상을 위한 블록 에너지 기반 적응적 이산 웨이블릿 변환
Adaptive Discrete Wavelet Transform Based on Block Energy for JPEG2000 Still Images
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초록
본 논문에서는 웨이블릿 변환에 기반을 둔 JPEG2000 정지영상의 압축 시도 시 웨이블릿 변환을 decomposition 하는 레벨과 이를 구성하는 블록의 활성도를 내포하는 에너지에 기반 하여 그 양에 따라 적응적으로 계수 변환 후 복원 시 효율적 자원 관리를 통하여 복잡도를 감소시키고 계산량을 줄이는 적응식 DWT 변환 기법을 제안하였다. 수많은 멀티미디어 응용 분야 또는 서비스 중의 하나인 디지털 카메라의 핵심 분야를 차지하고 있는 정지영상 압축 분야에서의 최첨단 기술을 꼽으라면 단연 JPEG2000 표준을 이용한 압축, 전송의 응용 분야이다. JPEG2000 기반의 정지영상 압축 전송 표준의 핵심을 이루고 있는 웨이블릿 변환은 기존의 JPEG 표준에 사용된 이산 코사인 변환의 약점인, 복원 시 나타나는 블록킹 문제를 해결한 대안이다. 적응식 DWT 변환을 거친 정지영상이 복원된 후 일반적인 과정의 웨이블릿 변환 후 복원된 영상간의 MSE(Mean Square Error), PSNR(Peak Signal to Noise Ratio), 0의 계수의 개수 등을 비교하여 본 연구에서 제안된 에너지 기반의 적응적 웨이블릿 변환의 우수성을 연산 속도를 계산함으로써 검증하였다.
Abstract
The proposed algorithm in this paper is based on the wavelet decomposition and the energy computation of composed blocks so the amount of calculation and complexity is minimized by adaptively replacing the DWT coefficients and managing the resources effectively. We are now living in the world of a lot of multimedia applications for many digital electric appliances and mobile devices. Among so many multimedia applications, the digital image compression is very important technology for digital cameras to store and transmit digital images to other sites and JPEG2000 is one of the cutting edge technology to compress still images efficiently. The digital camera technology is mainly using the digital image compression features so that those images could be efficiently saved locally and transferred to other sites without any losses. JPEG2000 standard is applicable for processing the digital images usefully to keep, send and receive through wired and/or wireless networks. The discrete wavelet transform (DWT) is one of the main differences to the previous digital image compression standard such as JPEG, performing the DWT to the entire image rather than splitting into many blocks. Several digital images are tested with this method and restored to compare to the results of conventional DWT which shows that the proposed algorithm get the better result without any significant degradation in terms of MSE & PSNR and the number of zero coefficients when the energy based adaptive DWT is applied.
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