本文選題：視網(wǎng)膜 + 顏色視覺�。� 參考：《電子科技大學》2017年博士論文

【摘要】：視覺,是客觀世界在視網(wǎng)膜上的投影由視神經(jīng)系統(tǒng)處理加工后所產(chǎn)生的主觀感覺。視覺研究的終極目標是闡明這一主觀感覺產(chǎn)生的過程。研究視覺,不僅有利于了解視覺神經(jīng)系統(tǒng)的工作機制,認識人類自身,也有利于提高圖像采集和處理技術,為人工智能機器提供輸入。本文從計算模型的角度出發(fā),按照基于生理、面向任務、可計算、系統(tǒng)最簡的思路,結合計算機視覺中顏色恒常、有霧圖像去霧增強以及高動態(tài)范圍圖像顯示等三個具體應用,探討視網(wǎng)膜完成顏色恒常、圖像增強以及亮度動態(tài)范圍壓縮等視覺任務的可能機制。在顏色恒常中,本文引入水平細胞對視錐輸出的調節(jié)作用和視網(wǎng)膜神經(jīng)節(jié)細胞非經(jīng)典感受野動態(tài)亞區(qū)結構,通過模擬水平細胞對視錐細胞的大范圍調節(jié),神經(jīng)節(jié)細胞的中心外周顏色拮抗響應,神經(jīng)節(jié)細胞非經(jīng)典感受野亞區(qū)結構去抑制作用,神經(jīng)節(jié)細胞動態(tài)適應等視網(wǎng)膜機制中與顏色恒常高度相關的部分,提出一種無需顯式估計光源的顏色不變性計算模型。該模型的主要創(chuàng)新在于,通過神經(jīng)節(jié)細胞非經(jīng)典感受野亞區(qū)結構在保持對物體表面響應的同時選擇性地抑制光源,通過動態(tài)適應機制根據(jù)場景特征選擇抑制權重保證對不同場景的適應性。該模型與現(xiàn)有顏色恒常算法相比極有競爭力的比較結果說明,水平細胞對視錐信號的調整和神經(jīng)節(jié)細胞動態(tài)適應的非經(jīng)典感受野亞區(qū)去抑制作用在生物的顏色恒常能力中發(fā)揮了重要作用。在圖像去霧增強中,本文部分參考大氣散射模型對有霧圖像成因的描述,通過模擬雙極細胞高斯差感受野、無長突細胞根據(jù)視桿輸出對視錐雙極細胞輸出的動態(tài)調整、視網(wǎng)膜神經(jīng)節(jié)細胞非經(jīng)典感受野去抑制作用以及ON/OFF通路整合等視網(wǎng)膜機制中與圖像增強有關的部分,提出一種無需對環(huán)境進行顯式先驗假設的有霧圖像去霧增強模型。該模型的主要創(chuàng)新在于,利用視網(wǎng)膜不同層次的細胞分別處理有霧圖像的不同衰減,為單幅圖像去霧增強提供一種簡單直接的快速算法。該模型與現(xiàn)有去霧算法極有競爭力的比較結果說明,雙極細胞、無長突細胞以及神經(jīng)節(jié)細胞在視覺系統(tǒng)信號增強中有著一定的貢獻。在高動態(tài)范圍圖像顯示中,本文引入隨局部亮度動態(tài)變化的水平細胞感受野,通過模擬水平細胞動態(tài)感受野和雙極細胞高斯差感受野等視網(wǎng)膜機制中與亮度動態(tài)范圍壓縮相關的部分,提出一種在低動態(tài)范圍輸出設備上顯示高動態(tài)范圍圖像的色調映射方法。該方法的主要創(chuàng)新在于,通過模仿水平細胞根據(jù)亮度動態(tài)變化的感受野,有效避免在處理高光區(qū)域時出現(xiàn)光暈現(xiàn)象,同時利用雙極細胞高斯差感受野濾除場景冗余信息增強局部對比度。與視覺系統(tǒng)在不同自然光照環(huán)境下快速獲得穩(wěn)定感知的能力一致,該方法在不同場景中均有著穩(wěn)定的表現(xiàn)。該方法與現(xiàn)有色調映射算法極有競爭力的比較結果說明,水平細胞對視錐輸出的側抑制和雙極細胞帶通濾波的高斯差感受野有效地壓縮了輸入信號的動態(tài)范圍,有利于視覺系統(tǒng)以有限的資源處理動態(tài)范圍極大的輸入信號。本文通過三個描述不同視網(wǎng)膜機制的計算模型分別探討了視網(wǎng)膜在完成顏色恒常、圖像增強以及亮度動態(tài)范圍壓縮等視覺任務中的作用,整合這些不同生理機制,建立完整描述視網(wǎng)膜功能的統(tǒng)一多任務模型是今后進一步研究工作的方向和重點。
[Abstract]:Vision is the subjective sensation that the projection of the objective world on the retina is processed by the optic nerve system. The ultimate goal of the visual study is to clarify the process of the subjective sensation. From the point of view of the model, three specific applications such as color constancy, fogging enhancement and high dynamic range image display in the computer vision are used to explore the color constancy of the retina, and the color constancy of the retina is discussed. The possible mechanisms of visual tasks such as enhancement and luminance dynamic range compression. In color constancy, this paper introduces the regulation of the horizontal cells to the cone output and the dynamic subregion of the non classical receptive field of retinal ganglion cells. By simulating the wide range regulation of the cones of the horizontal cells and the central peripheral facial features of the ganglion cells. The response of color antagonism, ganglion cells non classical sensing of the structure of the wild sub region, the dynamic adaptation of ganglion cells in the retina mechanism related to the color constancy, and proposed a color invariance calculation model without explicit estimation of the light source. The main innovation of the model lies in the non classical receptive field of ganglion cells. The subregion structure, while maintaining the response to the surface of the object, selectively inhibits the light source and selects the inhibition weight to ensure the adaptability to different scenes by the dynamic adaptation mechanism according to the scene characteristics. The model is very competitive compared with the existing color constancy algorithm, which shows the adjustment of the conical signal and ganglion in the horizontal cell. In the image demogging enhancement, this paper describes the formation of the fog images in the atmospheric scattering model, through the simulation of the Gauss difference receptive field of the bipolar cell, and the non amacrine cell based on the optic pole output to the cone bipolar bipolar disorder. The dynamic adjustment of cell output, the inhibition of the non classical receptive field of retinal ganglion cells and the part of the image enhancement related to the retinal mechanism of ON/OFF pathway integration, propose a fogging enhancement model without the explicit prior assumption of the environment. The main innovation of this model is the use of different retina. The hierarchical cells treat the different attenuation of foggy images and provide a simple and direct algorithm for single image fog enhancement. The comparison results of this model with the existing fogging algorithms show that bipolar cells, no amacrine cells and ganglion cells have a certain contribution to the enhancement of visual system signal. In the state range image display, this paper introduces a horizontal cell receptive field with dynamic changes in local luminance, and presents a high dynamic range image on low dynamic range output devices by simulating the parts related to the dynamic range compression of the luminance dynamic range, such as the dynamic receptive field of horizontal cells and the Gauss differential receptive field of bipolar cells. The main innovation of this method is that by imitating the receptive field of the dynamic change of luminance by the horizontal cells, the halo phenomenon can be avoided in the high light region, and the local contrast is enhanced by using the bipolar cell Gauss difference receptive field to filter the scene redundancy information. The ability of fast obtaining stable perception is consistent, and the method has a stable performance in different scenarios. The comparison results with the existing hue mapping algorithm show that the Gauss differential field of horizontal cells to the cone output side suppression and the bipolar cell band pass filter effectively compresses the dynamic model of the input signal. It is beneficial for the visual system to deal with the dynamic range of input signals with limited resources. In this paper, the functions of retina in visual tasks such as color constancy, image enhancement and luminance dynamic range compression are discussed respectively by three computational models describing different retinal mechanisms, and these different physiological mechanisms are integrated. The unified multitask model describing retinal function is the direction and emphasis of further research.
【學位授予單位】：電子科技大學
【學位級別】：博士
【學位授予年份】：2017
【分類號】：R339.14;TP391.41

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相關博士學位論文 前1條

1 杜馨瑜;模擬視覺機制的圖像處理若干問題研究[D];電子科技大學;2012年

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本文編號：1982810