In dynamic background , people commonly care about some objects , which have a strong wallop to people ' s system of vision or are special object regarded as important things by people 通常，在复杂的背景中，人们更加关心的往往是对人类视觉系统具有很强冲击性的目标或者是人们要特别关注的目标，因此对于该目标的综合处理变得尤为关键。
At the other hand , human eyes are the receptor of the image , so it is very important to study the characteristics of human vision system when we try to design a new coding algorithm 因此， 2000年诞生了基于小波变换的更高压缩率以及更多新功能的新一代静态图像压缩标准jpeg2000 。另一方面，眼睛是图像的感受者，人类视觉系统的特征对图像编码起重要的作用。
Jpeg2000 is based on wavelet transform which provides multi - resolution analyses similar to the multi - channel decomposition of human vision . in this paper , we firstly summarize the basic principles and some popular methods of digital image compression 由于jpeg2000是基于小波变换的编码，提供了类似人类视觉系统的多通道空频分解，为视觉模型应用提供了一个良好的平台。
Texture is an important feature in many nature sceneries , remote sensing , medical image and many other types of images . perception texture plays a crucial role for activities of recognition and representation in the human vision system 纹理是自然景物图像、遥感图像、医学图像和其它图像的一个重要特征，对纹理的感知在人类视觉系统进行识别和解释活动中起着重要的作用。
This paper employed the characteristics of the hvs ( human visual system ) responded to the image contents and realized the two kinds of image - adaptive watermark algorithm , one is in the spatial domain based on the statistics theory and another in the dct domain with meaningful digital watermark 本文利用hvs人类视觉系统模型，提出了图像内容自适应的数字水印算法，分别实现了时空域中的统计原理水印算法和dct变换域中的有意义水印算法。
Algorithms of video segmentation that are good adaptive character and real time are crucial to the final mpeg 4 coding products there exist the contributions in this dissertation as follows obtaining the edge of video objects is crucial to the video segmentation , author researches the features of human being visual , especially giving a description of mach band that is usually used in the image processing , and builds a model of mathematics , researching the mach band of color image ( 1 )视频分割的关键是获得视频对象的边界，边缘检测很重要,本论文以人类的视觉系统的特性为出发点，对图像处理中经常应用的马赫带现象进行了详尽的分析并进行了数学建模，研究分析了彩色图像的马赫带现象。在对马赫带图像分析的基础上，得出了人类视觉系统对图像边缘能识别的最小灰度差和彩色差曲线。
Automatic threshold choice is difficult and important to color images edge detection , first of all , on the base of human visual properties , threshold versus intensity function of human visual system are researched and analyzed , by using method of mathematic modeling and the result of saturation research , function of least color difference that can be perceptible by visual systems in detecting edge is given 摘要自动阀值选取是彩色图像边缘检测的难点和关键问题，首先从人类的视觉特性出发，分析了人类视觉系统的亮度感知门限函数，利用数学建模方法和色度学方面的研究成果，给出人类视觉系统对彩色图像边缘所能识别的最小彩色差函数。
In order to improve coding efficiency at low bit - rates , this thesis adopted wavelet and nonlinear matching pursuit techniques , combined with some characteristics of human visual system , aimed at improve the performance of video coding at low bit - rates . the major contributions of this thesis are included in the following : 1 为了提高低速率编码效率，本文综合小波变换以及匹配跟踪非线性信号分解技术，并结合人类视觉系统hvs的各种特性，致力于提高视频编码算法在低速率条件下的编码性能，并对所涉及到的若干问题进行了探索和解决，并取得如下创新性研究成果： 1
Distribution of wavelet coefficients in those sub - images is just appropriate for the properties of human vision systerm . it is that eyes are most sensitive to sub - image in the low resolution ratio and less sensitive to sub - images in the high resolution ratio . so a little loss of information in high sub - images may not bring out marked change to vision effect of construct image 经分解后的各个子图中的小波系数的分布恰好适合人类视觉系统的特点，即人眼对于低分辨率子图更敏感，对于高分辨率子图较不敏感，因此高分辨率子图中的信息稍有损耗并不会显著影响重构后图像的视觉效果，这样实现图像的高压缩比就成为可能。
This article begin with analyzing the character of human vision , making use of the notion of system to balance the several technology targets , such as image quality , real - time capability , the cost of system and so on , and at the basis of thorough analysis toward the concrete technology target of the virtual real - time photographing system , putting forward the real - time portrait pick - up arithmetic based on human vision system 本文从分析人类视觉特征入手，运用系统的观念综合平衡图像质量、实时性、与系统成本等技术指标，在对虚拟实时照相系统具体技术指标深入分析的基础上，提出了基于人类视觉系统（ hvs ）特性的实时人像提取算法。
