一种高通量dPCR荧光图像自适应增强算法

目的 为了改善荧光图像背景光照不均匀和对比度低的问题,提出一种荧光图像自适应亮度校正和低对比度增强算法。方法 根据光照成像原理,利用引导滤波提取出荧光图像的光照分量,通过改进的二维Gamma函数动态校正背景光照,利用Top-hat变换分离出校正后的前景和背景,对前景进行自适应直方图均衡化,以实现荧光图像自适应增强的目的。结果 对比传统算法,文中算法处理后的图像背景光照均匀,对比度增强效果明显,其中标准差平均提高了9.4倍,平均梯度平均提高了1.2倍,信息熵平均提高了0.2倍。结论 文中算法可以改善高通量dPCR荧光图像背景光照不均匀性,提高图像对比度,突出图像中隐藏的细节,对其他荧光图像处理也具有参考价值。     

红外图像实时增强的新算法

针对红外图像的特点,提出了一种红外图像实时增强的新算法。该算法通过分析图像的直方图,得到图像中目标像素数峰值的估计值,并作为平台直方图均衡化的阈值。用该阈值对直方图进行修正,然后通过修正后的直方图进行直方图均衡化。在FPGA内通过采用并行处理结构及流水线技术实现了该算法,并且每秒可处理25帧128×128×8bits的红外图像。理论分析和实验结果均表明,本算法克服了采用一般直方图均衡化增强红外图像的缺点?对背景和噪声增强过度,抑制了目标的增强。该算法对红外图像增强后,图像对比度是直方图均衡化增强后图像对比度的1.8倍。     

增强AC PDP低灰度级图像的子场抖动方法

为增强交流等离子体显示器(AC PDP)中低灰度级图像的显示效果,提出了一种子场抖动方法。该方法根据ACPDP采用子场方法显示灰度的特点,利用一种新型阈值矩阵对AC PDP中权重较小的两个子场分别进行抖动处理。同时,设计实现了子场抖动电路,并将其与传统误差扩散电路分别应用于32英寸AC PDP上进行测试。实验结果表明,子场抖动方法在表达低灰度级图像时无条纹状噪声,对低灰度级图像的增强效果优于传统误差扩散方法。     

自适应红外图像直方图均衡增强算法

针对红外图像的特点,本文提出了一种自适应红外图像直方图均衡增强算法.该方法根据原始图像的直方图,自适应地构造出一个加权函数对原始图像的直方图进行加权处理,然后采用加权后的直方图对原始图像进行直方图均衡化.算法不需要人为指定阈值,而且克服了传统直方图均衡提升红外图像背景的缺点.实验结果表明,该算法对红外图像具有较好的增强效果,能够有效地抑制图像的背景,突出目标.     

一种微弱图像增强技术研究

对传统灰度图像直方图均衡化方法进行了深入研究,提出了一种基于正切函数调整的直方图均衡化改进算法,该方法有利于提高图像的对比度,达到对图像判别的要求。 算法实现的关键是最优参数选择,因此采用了一种便于选择最优参数的方法。 另外,将图像相似程度应用于了增强效果的评价,为图像增强的实验分析提供了新的方法,具有一定的科学性与可行性。 实验结果表明,该算法比现有的图像增强方法效果更好。     

基于小波变换与反锐化掩模的图像对比度增强

针对传统空间域图像对比度增强算法存在灰度级空间分配不合理和噪声敏感的问题,基于图像的局部细节信息分析,提出了一种新的基于小波变换和反锐化掩模(UM)的图像对比度增强算法.该算法以小波变换作为工具,运用反锐化掩模的思想,计算出代表局部细节信息且同时考虑了图像中的噪声信息的统计量,然后将这一新的统计量作为重新分配灰度级空间...     

表面放电型彩色AC-PDP对比度的提高

对驱动波形和制作在显示电极对间的黑条对表面放电型AC PDP对比度的影响进行了实验研究 ,结果表明 ,改进驱动波形和采用黑条技术是提高PDP暗室对比度和亮室对比度的有效措施。并且开发出一种新型电压波形用于 2 1英寸彩色AC PDP的驱动 ,得到高对比度和稳定的显示图像     

自适应红外图像直方图均衡增强算法

针对红外图像的特点,本文提出了一种自适应红外图像直方图均衡增强算法。该方法根据原始图像的直方图,自适应地构造出一个加权函数对原始图像的直方图进行加权处理,然后采用加权后的直方图对原始图像进行直方图均衡化。算法不需要人为指定阈值,而且克服了传统直方图均衡提升红外图像背景的缺点。实验结果表明,该算法对红外图像具有较好的增强效果,能够有效地抑制图像的背景,突出目标。     

表面放电型彩色AC—PDP对比度的提高

对驱动波形和制作在显示电极对间的黑条对表面放电型AC－PDP对比度的影响进行了实验研究，结果表明，改进驱动波形和采用黑条技术是提高PDP暗室对比度和亮室对比度的有效措施。并且开发出一种新型电压波形用于21英寸彩色AC－PDP的驱动，得到高对比度和稳定的显示图像。     

基于偏微分方程的非线性图像去噪增强技术研究

本文主要研究基于偏微分方程图像去噪增强。针对降质图像去噪增强问题,结合偏微分理论和图像去噪增强方法,改进P-M各向异性扩散模型,有效去噪并保留图像边缘信息。对于基于梯度场均衡化对比度增强的不足,结合偏微分和可调直方图均衡化,增强图像纹理并改善对比度,并客观质量评价处理后图像。     

PDP低灰度级图像反伽马校正色彩还原方法

为了解决等离子体显示器(PDP)反伽马校正中低灰度级增强引起的色彩失真和偏移,提出了一种低灰度级图像色彩还原方法。该方法先利用HSI色彩空间模型对图像的色调、饱和度、强度分量进行分析,得到了色调恒常性和RGB三色校正的关系,然后计算出图像低灰度级增强的色彩补偿参数。最后将所得参数从HSI转换到RGB色彩空间,直接对RGB三基色分量处理,有较好的实时性和硬件可实现性。实验结果表明,该方法解决了伽马校正中的低灰度级图像色调偏移和色彩失真现象,校正后的图像色调和饱和度误差均小于2.2%,具有很好的色彩显示效果。     

Image contrast enhancement with brightness preservation using an optimal gamma correction and weighted sum approach

The enhancement of image contrast and preservation of image brightness are two important but conflicting objectives in image restoration. Previous attempts based on linear histogram equalization had achieved contrast enhancement, but exact preservation of brightness was not accomplished. A new perspective is taken here to provide balanced performance of contrast enhancement and brightness preservation simultaneously by casting the quest of such solution to an optimization problem. Specifically, the non-linear gamma correction method is adopted to enhance the contrast, while a weighted sum approach is employed for brightness preservation. In addition, the efficient golden search algorithm is exploited to determine the required optimal parameters to produce the enhanced images. Experiments are conducted on natural colour images captured under various indoor, outdoor and illumination conditions. Results have shown that the proposed method outperforms currently available methods in contrast to enhancement and brightness preservation.     

Combination of wavelet transform and singular value decomposition-based contrast enhancement technique for target detection in UAV reconnaissance thermal images

In Aerial surveillance, thermal images acquired by unmanned aerial vehicle (UAV) are greatly affected due to various external interferences, which results in a low contrast image. Widely used conventional contrast enhancement methods such as histogram equalization and dynamic range partitioning techniques suffer from severe brightness changes and reduced sharpness, which in turn fail to preserve the edge details of the image. Thus for efficient target detection, it is essential to develop effective thermal infrared image contrast and edge enhancement technique. In this paper, wavelet transform (WT) and singular value decomposition (SVD)-based image enhancement technique is attempted for the target detection using thermal images captured by UAV. The discrete wavelet transform (DWT), stationary wavelet transform (SWT) and SVD are used for texture feature enhancement, edge enhancement and illumination correction, respectively. The experimental results show that the proposed technique yields higher entropy (6.7485), EMEE (2.1212), MSSIM (0.8719) and lower AMBE (21.9049) values when compared to other existing techniques.     

AC PDP高阻维持驱动方法

针对AC PDP传统维持驱动方法存在零电压状态,造成两次维持放电之间壁电荷损失的问题.本文提出了一种AC PDP高阻维持驱动方法,在该方法中,采用高阻状态替换了传统维持驱动方法中的零电压状态.从而去掉了两次维持放电中间的放电通路,使得壁电荷在两次维持放电之间不会损失.实验结果表明,采用该方法,可以增大AC PDP维持电压余裕度,降低维持电压,提高维持放电的稳定性.     

Contrast enhancement using real coded genetic algorithm based modified histogram equalization for gray scale images

Histogram equalization is a well‐known technique used for contrast enhancement. The global HE usually results in excessive contrast enhancement because of lack of control on the level of contrast enhancement. A new technique named modified histogram equalization using real coded genetic algorithm (MHERCGA) is aimed to sweep over this drawback. The primary aim of this paper is to obtain an enhanced method which keeps the original brightness. This method incorporates a provision to have a control over the level of contrast enhancement and applicable for all types of image including low contrast MRI brain images. The basic idea of this technique is to partition the input image histogram into two subhistograms based on a threshold which is obtained using Otsu's optimality principle. Then, bicriteria optimization problem is formulated to satisfy the aforementioned requirements. The subhistograms are modified by selecting optimal contrast enhancement parameters. Finally, the union of the modified subhistograms produce a contrast enhanced and details preserved output image. While developing an optimization problem, real coded genetic algorithm is applied to determine the optimal value of contrast enhancement parameters. This mechanism enhances the contrast of the input image better than the existing contemporary HE methods. The quality of the enhanced brain image indicates that the image obtained after this method can be useful for efficient detection of brain cancer in further process like segmentation, classification, etc. The performance of the proposed method is well supported by the contrast enhancement quantitative metrics such as discrete entropy and natural image quality evaluator. © 2015 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 25, 24–32, 2015     

Contrast enhancement dynamic histogram equalization for medical image processing application

Image processing requires an excellent image contrast‐enhancement technique to extract useful information invisible to the human or machine vision. Because of the histogram flattening, the widely used conventional histogram equalization image‐enhancing technique suffers from severe brightness changes, rendering it undesirable. Hence, we introduce a contrast‐enhancement dynamic histogram‐equalization algorithm method that generates better output image by preserving the input mean brightness without introducing the unfavorable side effects of checkerboard effect, artefacts, and washed‐out appearance. The first procedure of this technique is; normalizing input histogram and followed by smoothing process. Then, the break point detection process is done to divide the histogram into subhistograms before we can remap the gray level allocation. Lastly, the transformation function of each subhistogram is constructed independently. © 2011 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 21, 280‐289, 2011;     

基于NSST多尺度自适应的Retinex低照度图像增强算法

目的在对低照度图像进行增强时,针对传统频率域方法由于尺度不够丰富而不能很好保留图像高频细节的问题,提出一种基于NSST多尺度自适应的Retinex低照度图像增强算法。方法首先将低照度图像转化至HSI颜色空间后,单独对I通道进行处理,实现对图像色彩信息的保真效果;然后对I通道进行Retinex算法得到反射分量,从而去除照度信息对图像亮度的影响;对反射分量进行伽马调整后,进行基于La(平均亮度)、Pa(平均对比度)、Ia(信息熵)等3个特征值的自适应NSST分解,从而得到最佳参数的高频分量。结果在主观观察和客观无参考图像质量评价中,文中算法的增强效果和评价得分都要优于其他算法。结论经过自适应参数优化之后,低照度图像的对比度得到了提高,可视性和图像质量都得到了显著提升。     

保护膜材料对AC PDP放电特性影响的实验研究

提出了用测量ACPDP(ACplasmadisplaypanel)放电特性和加速老化特性来探求保护膜发射和稳定性能的间接测量方法 ,研制了模拟ACPDP放电特性测量装置 ,为衡量保护膜特性提供了有力的工具。并利用此装置对不同材料保护膜对ACPDP放电特性的影响进行了分析讨论 ,确定了新颖膜材的选择方向 ,探索了使用高发射性能保护膜材料所必须解决的问题