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Natural Color Image Enhancement Based on Modified Multiscale Retinex Algorithm and Performance Evaluation UsingWavelet Energy

机译:基于改进的多尺度视网膜算法的自然彩色图像增强与使用灯泡能量的性能评估

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This paper presents a new color image enhancement technique based on modified modified MultiScale Retinex (MSR) algorithm and visual quality of the enhanced images are evaluated using a new metric, namely, Wavelet Energy (WE). The color image enhancement is achieved by downsampling the value component of HSV color space converted image into three scales (normal, medium and fine) following the contrast stretching operation. These downsampled value components are enhanced using the MSR algorithm. The value component is reconstructed by averaging each pixels of the lower scale image with that of the upper scale image subsequent to upsampling the lower scale image. This process replaces dark pixel by the average pixels of both the lower scale and upper scale, while retaining the bright pixels. The quality of the reconstructed images in the proposed method is found to be good and far better then the other researchers method. The performance of the proposed scheme is evaluated using new wavelet domain based assessment criterion, referred as WE. This scheme computes the energy of both original and enhanced image in wavelet domain. The number of edge details as well as WE is less in a poor quality image compared with naturally enhanced image. Experimental results presented confirms that the proposed wavelet energy based color image quality assessment technique efficiently characterizes both the local and global details of enhanced image.
机译:本文介绍了一种基于改进的修改的多尺度视网膜(MSR)算法的新型彩色图像增强技术,并使用新的公制评估增强图像的视觉质量,即小波能量(我们)。通过将HSV颜色空间转换图像的值分量对比度拉伸操作之后的三个尺度(正常,中等和精细)进行采样来实现彩色图像增强。使用MSR算法增强了这些下采样值组件。通过在ups采样下测量图像之后的上刻度图像的每个像素来重建值分量来重建值分量。该过程通过较低比例和大规模的平均像素替换暗像素,同时保持明亮的像素。发现在所提出的方法中的重建图像的质量是良好的,更好的是另一个研究人员的方法。使用新的小波根据基于小波域的评估标准进行评估,评估所提出的方案的性能,推荐。该方案在小波域中计算原始和增强图像的能量。与自然增强的图像相比,边缘细节的数量以及我们的质量差。提出了实验结果证实,所提出的小波能量的彩色图像质量评估技术有效地表征了增强图像的本地和全球细节。

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