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Contrast Enhancement and Intensity Preservation for Gray-Level Images Using Multiobjective Particle Swarm Optimization

机译:基于多目标粒子群算法的灰度图像对比度增强和强度保持

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The contrast enhancement of gray-level digital images is considered in this paper. In particular, the mean image intensity is preserved while the contrast is enhanced. This provides better viewing consistence and effectiveness. The contrast enhancement is achieved by maximizing the information content carried in the image via a continuous intensity transform function. The preservation of image intensity is obtained by applying gamma-correction on the images. Since there is always a trade-off between the requirements for the enhancement of contrast and preservation of intensity, an improved multiobjective particle swarm optimization procedure is proposed to resolve this contradiction, making use of its flexible algorithmic structure. The effectiveness of the proposed approach is illustrated by a number of images including the benchmarks and an image sequence captured from a mobile robot in an indoor environment.
机译:本文考虑了灰度数字图像的对比度增强。特别地,在增强对比度的同时保留了平均图像强度。这样可以提供更好的观看一致性和有效性。对比度增强是通过连续强度变换函数最大化图像中携带的信息内容来实现的。通过在图像上进行伽玛校正,可以保持图像强度。由于在增强对比度和保持强度的要求之间总是要取舍,因此提出了一种改进的多目标粒子群优化程序来解决这一矛盾,并利用其灵活的算法结构。包括基准和从室内环境中的移动机器人捕获的图像序列在内的许多图像说明了所提出方法的有效性。

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