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Colour-Preserving Contrast Enhancement Algorithm for Images

机译:图像的保色对比度增强算法

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Conventional contrast enhancement techniques often fail to produce satisfactory results for low-contrast images, and cannot be automatically applied to different images because their processing parameters must be specified manually to produce a satisfactory result for a given image. This work presents a colour-preserving contrast enhancement (CPCE) algorithm for images. Modification to images was performed in the HSV colour-space. The Hue component is preserved (unchanged), luminance modified using Contrast Limited Adaptive Histogram Equalization (CLAHE), while Saturation components were up-scaled using a derived mapping function on the approximate components of its discrete wavelet transform. Implementation was done in MATLAB and compared with CLAHE and Histogram Equalization (HE) algorithms in the RGB colour space. Subjective (visual quality inspection) and objective parameters (Peak-signal-to-noise ratio (PSNR), Absolute Mean Brightness Error (AMBE) and Mean squared error (MSE)) were used for performance evaluation. The method produced images with the lowest MSE, AMBE, and highest PSNR when tested, yet preserved the visual quality of the image.
机译:常规的对比度增强技术对于低对比度图像通常无法产生令人满意的结果,并且不能自动应用于不同的图像,因为必须手动指定其处理参数才能对给定图像产生令人满意的结果。这项工作提出了一种图像的保色对比度增强(CPCE)算法。在HSV色彩空间中对图像进行修改。色相分量被保留(未更改),使用对比度受限的自适应直方图均衡化(CLAHE)进行了亮度修改,而饱和度分量则使用派生的映射函数对其离散小波变换的近似分量进行了按比例放大。实现是在MATLAB中完成的,并与RGB颜色空间中的CLAHE和直方图均衡(HE)算法进行了比较。主观(视觉质量检查)和客观参数(峰值信噪比(PSNR),绝对平均亮度误差(AMBE)和均方误差(MSE))用于性能评估。经测试,该方法产生的图像具有最低的MSE,AMBE和最高的PSNR,但仍保留了图像的视觉质量。

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