For low gray image, the float gray level codes are combined to the binary coded gray levels by the error diffusion method.
然后利用误差扩散方法将浮动灰度编码所包含的低灰度级图像信息融合到用于显示的子场编码中。
An improving noise eliminated difference template based on the analysis of object and background gray value also has been developed to eliminate the low frequency noise in image.
对图像中的低频噪声，基于对图像中目标与背景灰度值特点的分析，提出了改进的差分去噪声模板。
This paper introduces a new method of low contrast gray image enhancement based on PCNN after studying the operation elements and action mechanism of PCNN.
通过对PCNN工作原理和行为机制的深刻剖析，本文提出基于PCNN的低对比度的灰度图像增强算法。
The image enhancement problem for degraded images with less gray levels and low contrasts.
灰度等级少、对比度低的降质图像增强问题。
This paper proposes an algorithm, which by reasonable using the gray-level-statistics of fingerprint images, resolves the problem of fingerprint image segmentation with low computational cost.
通过合理地运用指纹图像的灰度特性，以较低的计算代价有效地解决了指纹图像的分割问题，从而使算法的处理效果好、运行速度快。
The characteristics of low light level (LLL) image were analyzed in aspects of imaging process gray level distribution and correlativity of picture element in space and time of LLL image.
从微光图像的成像过程、灰度分布和像素空间与时间相关性等几个方面对微光图像特征作较系统的分析。
This algorithm solves the problem of fingerprint image segmentation with low computational cost based on reasonable application of the gray-level-statistics of fingerprint images.
算法中通过合理的运用图像灰度特性，以较低的计算代价有效地解决了指纹图像分割问题。
A modulating fusion algorithm based on wavelet transform is advanced. The low light level image and infrared image are fused using contrast modulating and gray level modulating method.
提出了一种基于小波变换的微光图像与红外图像的调制融合算法，用对比度调制与灰度调制方法分别对微光图像与红外图像进行了融合处理。
With nonlinear transformation, the high-resolution gray image was compressed to low gray-resolution image, so the detail variation of spectrum would be better reflected.
该方法通过非线性变换，将高灰度分辨率图像压缩为低灰度分辨率图像，能更好地体现语谱图的细微变化。
With nonlinear transformation, the high-resolution gray image was compressed to low gray-resolution image, so the detail variation of spectrum would be better reflected.
该方法通过非线性变换，将高灰度分辨率图像压缩为低灰度分辨率图像，能更好地体现语谱图的细微变化。
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