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Colour-Preserving Contrast Enhancement Algorithm for Images

机译:图像的颜色保留对比度增强算法

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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:传统的对比度增强技术通常不能产生令人满意的低对比度图像的结果,并且不能自动应用于不同的图像,因为必须手动指定它们的处理参数以产生给定图像的令人满意的结果。这项工作提出了一种用于图像的色彩保留对比度增强(CPCE)算法。在HSV颜色空间中执行对图像的修改。 Hue组件被保留(不变),使用对比度有限的自适应直方图均衡(CLAHE)修改的亮度,而在其离散小波变换的近似分量上使用导出的映射函数来缩放饱和分量。在MATLAB中完成实施,并与RGB颜色空间中的CLAHE和直方图均衡(HE)算法进行比较。主观(视觉质量检测)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。该方法在测试时产生了具有最低MSE,AMBE和最高PSNR的图像,但保留了图像的视觉质量。

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