3 . utilizing the hvs and the characteristic which integer wavelet analyzes the high - frequency coefficient to express the image detail , proposed the definition of energy coefficient . according to the sub - blocks from different groups , the computed energy coefficients were different 3 .利用人眼视觉模型和整数小波分解后高频系数表示图像细节的特性,提出了能量系数的定义,根据不同组的子块,计算出的能量系数是不相同的。
So this part is dealt with separately . dcpm method is employed to improve the quality of image coding with making full of the relativity of the wavelet coefficients . according to the different importance degree and vision character of the high frequency wavelet coefficients , different thresholds are applied to remove small coefficients ; then mannos module are applied to remove the visual redundancy ; in order to produce more zero - tree , horizontal and vertical wavelet coefficients are transformed accordingly to improve the compression ratio 对于小波变换后的小波系数的高频部分，根据其分布特性和人眼的视觉特性，采用视觉模型对零树量化过程的阈值进行修正，有效地去除视觉冗余；对各高频子图采用多级树集合分割的零树编码方法，有效地利用系数编码剩余符号，进一步提高压缩比。
According to the installation of the camera on the hebut - i mobile robot , analyzing the stereo vision model of lateral camera in detail in this thesis . at the same time , common visible region and the model error of this model are studied deeply , further more , the error produced by the error of the correspondence is analyzed in detail 并按照hebut -型移动机器人视觉系统中摄像机的配置关系，详细分析了摄像机横向配置的立体视觉模型，对该模型的共同可视范围、模型误差进行了深入的研究，同时对由于摄像机的配准误差而产生的误差进行了分析。
First , the coefficients of wavelet are quantized by the threshold formed by the eye ' s sensitivity to it ' s subband . then , wavelet coefficients are encoded by the entropy encoder , with the contexts formed by quantizing their prediction values , which are determined by their neighbors in space and time dimensions 它首先利用人眼视觉模型( hvs )对子带的系数进行量化；然后利用空间和时间相邻的系数对当前系数进行预测，以预测值的量化值作为上下文，对系数进行基于上下文的算术编码。
The equations derived are more complicated if more precise model is employed for high accuracy . the technique , which does n ' t need to have an explicit model - calibration based on neural networks implicit vision model , is more effective . since bp neural network can implement any nonlinear relationship from input to output and need n ' t to model , and the classical stereo vision approach based on explicit model are very complicated , an algorithm of stereo vision based on bp neural networks implicit vision model is proposed 利用神经网络可以充分逼近任意的非线性关系且无须精确建模的特点，针对传统的立体视觉方法过程繁琐，对安装精度要求高的不足，本文提出了一种基于bp神经网络隐式视觉模型的立体视觉方法，该算法实施起来比较简便；针对已有的像差修正算法计算过程复杂的不足，提出了一种基于bp神经网络的修正成像误差的算法；针对具有共面特征的点的三维重构的应用，提出了一种基于径向基函数网络的二维平面测量算法。
This arithmetic divides the wavelet coefficients of carrier image into 27 - classes by the background luminance , the texture and the edge mask character of visual system ; then after encrypting watermark image with magic cube transformation , the ycbcr model is employed , it embeds the watermark sequences in the carrier image with different intensity according to the coefficients " classes of carrier image in y channel 首先，将载体rgb图像转换到ycbcr颜色空间，然后提取亮度通道y ，将其进行小波变换，然后利用人眼视觉模型对载体图象分解后的小波系数进行分类。其次，对有意义的水印图像分别进行3次不同的魔方置乱，得到3个随机水印序列。
Regarding the precision requirement of the system , a simple linear camera model is selected and a calibration method based on grid image is proposed . based on linear camera model , this paper constructed a stereo vision model and designed an algorithm for 3 - dimensional coordinates " calculation through four cameras 论文提出了基于网格标记的线性摄象机的标定方法，建立了基于线性摄象机模型的立体视觉模型，并设计了四台摄象机匹配进行空间点三维坐标计算的算法。
