视觉功能修复中的图像和信号处理方法研究
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摘要
视觉是人类获取外界信息最主要的方式，视觉功能异常对患者的生活质量有很大影响。针对这些异常的视觉功能修复既是提高人们生活水平的重大需求，也面临很多重大的困难和挑战。
在各类视觉功能异常中，失明是程度最严重的一类，而色觉异常则是影响范围很大的一类。这两类视觉功能异常的修复方法都处于探索阶段，有很多需要解决的问题。
本文对这两类视觉功能异常的修复方案中的图像和信号处理方法进行了研究，主要包括以下方面：
(1)针对已有的二色觉者颜色感知模拟方法计算复杂度高的问题，提出了一种基于矩阵变换的二色觉者颜色感知模拟方法，比传统方法更加快速简单，有利于大量图像的处理。针对已有方法在模拟异常三色觉者感知方面的空白，提出了一种基于加权平均的异常三色觉者颜色感知模拟方法，可以模拟不同类别和程度的异常三色觉者的颜色感知。
(2)在对色觉异常的辅助矫正方法的研究中，提出了一种利用人工神经网络训练来重建异常视锥细胞信号的方法，从理论上说明了利用异常视锥细胞传递的信号可以重建出正常视锥细胞应有的信号。针对已有的基于颜色变换的色觉异常矫正方法颜色利用率低、自适应性不好的问题，提出了一种自组织颜色变换方法，自适应地将图像中的颜色变换成为二色觉者能够获取更多信息的颜色，显著增强二色觉者对颜色的分辨能力。
(3)研究了盲人视觉修复工程中对图像边缘检测的需求。针对已有方法在噪声环境下检测性能明显下降的不足，提出了颜色分布相似性和方向一致性这两类用于彩色图像边缘检测的新特征，并提出了多特征融合的彩色图像边缘检测方法，具有较好的抗噪性。在分析特征时，针对传统直方图相似性度量在直方图发生偏移的情况下准确性不高的问题，提出了一种基于平均窗口平移的直方图相似性度量，在图像受光照、噪声等因素影响而发生直方图偏移的情况下仍能正确度量直方图的相似性。
(4)研究了盲人视觉修复工程中对图像中目标轮廓分离的需求。提出了一种基于特征聚类的轮廓提取和分离方法，分别采用K-均值聚类和自组织映射的方法对边缘进行聚类，自动实现轮廓的提取、不同轮廓之间的分离以及轮廓与背景边缘之间的分离。在此基础上，提出一种自组织特征映射模型，来模拟视觉系统对彩色场景进行初步处理的机制，模型能够同步完成前景与背景分割、边缘检测、目标轮廓提取以及不同类别物体的分离等功能，为进一步研究视觉系统的信号处理机制提供了参考。
(5)为了寻找视觉修复工程中合适的神经刺激方式，对视觉信息的神经编码方式进行了研究。提出了一种基于同步振荡的轮廓提取和分离模型，通过神经振荡的同步和异步来区分不同物体的轮廓，不仅有助于对视觉系统中信息编码方式的研究，也为基于视神经刺激的盲人视觉修复项目中刺激方式的选择提供了参考。
本文提出的各类方法以视觉系统的特性和处理机制为依据，既具有较好的通用性，适合图像处理的各种应用，也具有一定的针对性，密切结合了视觉功能修复方案的需求，有望为针对失明和色觉异常的视觉功能修复提供帮助，从而为患者带来新的希望。
Vision is the most important way for human beings to obtain the information ofthe world.Vision abnormality affects the quality of life of sufferers.Therehabilitation of vision is the requirement of improving their living standard.However,it faces many difficulties and challenges.
Blindness is the most severe kind of vision abnormality,while color visiondeficiency is another kind of vision abnormality that has a wide influence range.Therehabilitation schemes for these two kinds of vision abnormality are still in theexploratory stage,and hence have many problems to be solved.
This dissertation focuses on image and signal processing methods in visionrehabilitation schemes for color vision deficiency and blindness.Studies have beencarried out in following aspects.
(1) To simulate the color perception of dichromats and avoid the highcomputation cost of conventional methods,a new simulation method is proposedbased on the matrix transformation.The method is easier and quicker than existingmethods and thereby fits for the processing of large amount of images.To make upthe absence of perception simulation for anomalous trichromats,a weighted averagemethod is proposed to simulate the color perception of anomalous trichromats withdifferent types and severities.
(2) During the investigation of color vision rectification,an artificial neuralnetwork model is proposed to rebuild response signals of abnormal cones by training,which indicates that normal cone response signals can be rebuilt from abnormal coneresponse signals.To solve the problems of low color utilization rate and adaptabilityin previous color transformation methods for color vision rectification,aself-organizing color transformation method is proposed.The method adaptivelychanges colors of a scene into discernable ones for dichromats,so as to enhance theircolor discrimination.
(3) Studies for the edge detection have been made according to the requirementof vision rehabilitation project for the blind.To alleviate the performancedegradation of the edge detection under noisy environments,two new features,named as color distribution similarity and orientation consistency respectively,areexploited in the edge detection.Accordingly,a feature fusion method is proposed for the edge detection of color images.The method has a better performance thanconventional ones under noisy environments.
When calculating features,general histogram similarity measures havedisadvantages when several kinds of deformation happen to histograms.A novelsimilarity measure is proposed based on the average translation of histogram bins.The measure of average translation of bins outperforms general measures in thecondition of histogram deformation caused by illumination variance or noise of theimage.
(4) Studies for the contour extraction and separation have been made accordingto the requirement of vision rehabilitation project for the blind.A novel method isproposed to separate individual object contours in an image by clustering edges withdifferent local features.The method adopts the k-means clustering and the SOMrespectively to group edge pixels with similar features,in order to extract contours,separate different object contours,and separate contours from the background.
Based on this study,a self-organizing feature map model is proposed tosimulate the visual processing mechanism for color scenes.The model cansimultaneously fulfill multiple tasks such as the figure-ground separation,the edgedetection,the contour extraction,and the object separation.It helps for furtherinvestigating the signal processing mechanism of the visual system.
(5) To find appropriate neural stimulating methods in the vision rehabilitationproject for the blind,the neural encoding mode for the visual information has beeninvestigated.A coherent oscillation model for the contour extraction and separationis proposed.This model can extract and separate contours of different objects bysynchronization and asynchronization of neural oscillation.It helps to promote theinvestigation on the neural encoding mode for the visual information,and alsoprovides suggestions for the selection of neural stimulating methods in the visionrehabilitation project.
All proposed methods in this dissertation are based on characteristics andmechanisms of vision system.They have both good versatility for different imageprocessing applications and specific advantages for vision rehabilitation schemes.Itis expected to provide help to the vision rehabilitation for color vision deficiency andblindness,and thus bring new hope to sufferers.
在各类视觉功能异常中，失明是程度最严重的一类，而色觉异常则是影响范围很大的一类。这两类视觉功能异常的修复方法都处于探索阶段，有很多需要解决的问题。
本文对这两类视觉功能异常的修复方案中的图像和信号处理方法进行了研究，主要包括以下方面：
(1)针对已有的二色觉者颜色感知模拟方法计算复杂度高的问题，提出了一种基于矩阵变换的二色觉者颜色感知模拟方法，比传统方法更加快速简单，有利于大量图像的处理。针对已有方法在模拟异常三色觉者感知方面的空白，提出了一种基于加权平均的异常三色觉者颜色感知模拟方法，可以模拟不同类别和程度的异常三色觉者的颜色感知。
(2)在对色觉异常的辅助矫正方法的研究中，提出了一种利用人工神经网络训练来重建异常视锥细胞信号的方法，从理论上说明了利用异常视锥细胞传递的信号可以重建出正常视锥细胞应有的信号。针对已有的基于颜色变换的色觉异常矫正方法颜色利用率低、自适应性不好的问题，提出了一种自组织颜色变换方法，自适应地将图像中的颜色变换成为二色觉者能够获取更多信息的颜色，显著增强二色觉者对颜色的分辨能力。
(3)研究了盲人视觉修复工程中对图像边缘检测的需求。针对已有方法在噪声环境下检测性能明显下降的不足，提出了颜色分布相似性和方向一致性这两类用于彩色图像边缘检测的新特征，并提出了多特征融合的彩色图像边缘检测方法，具有较好的抗噪性。在分析特征时，针对传统直方图相似性度量在直方图发生偏移的情况下准确性不高的问题，提出了一种基于平均窗口平移的直方图相似性度量，在图像受光照、噪声等因素影响而发生直方图偏移的情况下仍能正确度量直方图的相似性。
(4)研究了盲人视觉修复工程中对图像中目标轮廓分离的需求。提出了一种基于特征聚类的轮廓提取和分离方法，分别采用K-均值聚类和自组织映射的方法对边缘进行聚类，自动实现轮廓的提取、不同轮廓之间的分离以及轮廓与背景边缘之间的分离。在此基础上，提出一种自组织特征映射模型，来模拟视觉系统对彩色场景进行初步处理的机制，模型能够同步完成前景与背景分割、边缘检测、目标轮廓提取以及不同类别物体的分离等功能，为进一步研究视觉系统的信号处理机制提供了参考。
(5)为了寻找视觉修复工程中合适的神经刺激方式，对视觉信息的神经编码方式进行了研究。提出了一种基于同步振荡的轮廓提取和分离模型，通过神经振荡的同步和异步来区分不同物体的轮廓，不仅有助于对视觉系统中信息编码方式的研究，也为基于视神经刺激的盲人视觉修复项目中刺激方式的选择提供了参考。
本文提出的各类方法以视觉系统的特性和处理机制为依据，既具有较好的通用性，适合图像处理的各种应用，也具有一定的针对性，密切结合了视觉功能修复方案的需求，有望为针对失明和色觉异常的视觉功能修复提供帮助，从而为患者带来新的希望。
Vision is the most important way for human beings to obtain the information ofthe world.Vision abnormality affects the quality of life of sufferers.Therehabilitation of vision is the requirement of improving their living standard.However,it faces many difficulties and challenges.
Blindness is the most severe kind of vision abnormality,while color visiondeficiency is another kind of vision abnormality that has a wide influence range.Therehabilitation schemes for these two kinds of vision abnormality are still in theexploratory stage,and hence have many problems to be solved.
This dissertation focuses on image and signal processing methods in visionrehabilitation schemes for color vision deficiency and blindness.Studies have beencarried out in following aspects.
(1) To simulate the color perception of dichromats and avoid the highcomputation cost of conventional methods,a new simulation method is proposedbased on the matrix transformation.The method is easier and quicker than existingmethods and thereby fits for the processing of large amount of images.To make upthe absence of perception simulation for anomalous trichromats,a weighted averagemethod is proposed to simulate the color perception of anomalous trichromats withdifferent types and severities.
(2) During the investigation of color vision rectification,an artificial neuralnetwork model is proposed to rebuild response signals of abnormal cones by training,which indicates that normal cone response signals can be rebuilt from abnormal coneresponse signals.To solve the problems of low color utilization rate and adaptabilityin previous color transformation methods for color vision rectification,aself-organizing color transformation method is proposed.The method adaptivelychanges colors of a scene into discernable ones for dichromats,so as to enhance theircolor discrimination.
(3) Studies for the edge detection have been made according to the requirementof vision rehabilitation project for the blind.To alleviate the performancedegradation of the edge detection under noisy environments,two new features,named as color distribution similarity and orientation consistency respectively,areexploited in the edge detection.Accordingly,a feature fusion method is proposed for the edge detection of color images.The method has a better performance thanconventional ones under noisy environments.
When calculating features,general histogram similarity measures havedisadvantages when several kinds of deformation happen to histograms.A novelsimilarity measure is proposed based on the average translation of histogram bins.The measure of average translation of bins outperforms general measures in thecondition of histogram deformation caused by illumination variance or noise of theimage.
(4) Studies for the contour extraction and separation have been made accordingto the requirement of vision rehabilitation project for the blind.A novel method isproposed to separate individual object contours in an image by clustering edges withdifferent local features.The method adopts the k-means clustering and the SOMrespectively to group edge pixels with similar features,in order to extract contours,separate different object contours,and separate contours from the background.
Based on this study,a self-organizing feature map model is proposed tosimulate the visual processing mechanism for color scenes.The model cansimultaneously fulfill multiple tasks such as the figure-ground separation,the edgedetection,the contour extraction,and the object separation.It helps for furtherinvestigating the signal processing mechanism of the visual system.
(5) To find appropriate neural stimulating methods in the vision rehabilitationproject for the blind,the neural encoding mode for the visual information has beeninvestigated.A coherent oscillation model for the contour extraction and separationis proposed.This model can extract and separate contours of different objects bysynchronization and asynchronization of neural oscillation.It helps to promote theinvestigation on the neural encoding mode for the visual information,and alsoprovides suggestions for the selection of neural stimulating methods in the visionrehabilitation project.
All proposed methods in this dissertation are based on characteristics andmechanisms of vision system.They have both good versatility for different imageprocessing applications and specific advantages for vision rehabilitation schemes.Itis expected to provide help to the vision rehabilitation for color vision deficiency andblindness,and thus bring new hope to sufferers.
引文
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