以人類視覺系統和模糊化控制為基礎的影像編解碼器

Abstract

本論文提出一個以人類視覺系統和模糊化控制為基礎的嶄新影像壓縮方法 。考慮在人類視覺中對於背景亮度和空間頻率的敏感性，此一視覺模式成 功的應用在影像壓縮，經由視覺模式的加入，其處理效能較一般影像處理 系統在主觀的視覺品質上有顯著的提昇。這影像壓縮系統包括離散餘弦轉 換，加以人類視覺系統和模糊化控制 為基礎的轉換係數量化以及可變長 度編碼，還原影像的品質好壞主要在於離散餘弦係數的量化上，因此我們 也完成了以人類視覺系統和模糊化控制為基礎的量化器的超大型積體電路 的架構設計，並利用計算機輔助設計工具完成電路佈局，摹擬及驗證。 In this thesis a novel processing schemes for gray level image compression based on the human visual system(HVS) and fuzzy control is proposed. The spatial model of the threshold vision that incorporates the masking processes takes account of two major sensitivities of the human visual system, namely background illumination levels and spatial frequency sensitivities. The distortion measures use common sense fuzzy rules for image quality prediction. The human visual models have been successfully applied in image compression. By the addition of the visual model, performance of these systems have a visible improvement of subject quality depending on visual perception. The image compression system contains discrete consine transform(DCT), quantization of DCT coefficients based on HVS and fuzzy control, and variable-length coding. The main feature to reconstructed image quality is the quantization of the DCT coefficients. So we also proposed an architecture of quantizer that are based on HVS and fuzzy control for VLSI implementation. The layout is designed under full custom design, and the chip are verified with "IRSIM".