Towards hardware-friendly retinex algorithms

Nikola Banić, S. Lončarić
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引用次数: 4

Abstract

Retinex theory was among the first to introduce a model for simultaneous brightness adjustment and removal of illumination influence on image colors by supposedly emulating some aspects of the human visual system's behaviour. The main idea of most Retinex methods is to readjust color channel values of individual pixels with respect to their local white references. Recently the Smart Light Random Memory Sprays Retinex (SLRMSR) method with a O(1) per-pixel complexity was proposed. Although theoretically fast, like with many other Retinex methods, the problem is that its local pixel sampling scheme and some of its local maximum calculation structures common to other Retinex methods as well are not particularly hardware-friendly. In this paper a reduced sampling scheme and an approximated local maxima calculation are proposed and included into a modified SLRMSR. While the resulting images are visually very similar to the ones obtained by the original SLRMSR, the modified SLRMSR is structurally simpler and more hardware friendly. The results are presented and discussed.
对硬件友好的视网膜算法
视网膜理论是第一个引入同时调节亮度和消除光照对图像颜色影响的模型,通过模拟人类视觉系统行为的某些方面。大多数Retinex方法的主要思想是重新调整单个像素相对于其局部白色参考的颜色通道值。近年来,提出了一种复杂度为0(1)的智能光随机记忆喷雾(SLRMSR)方法。虽然理论上快速,像许多其他Retinex方法一样,问题是它的局部像素采样方案和一些局部最大值计算结构与其他Retinex方法一样,不是特别硬件友好。本文提出了一种简化的采样方案和一种近似的局部极大值计算方法,并将其纳入改进的SLRMSR中。虽然生成的图像在视觉上与原始SLRMSR获得的图像非常相似,但修改后的SLRMSR在结构上更简单,并且对硬件更友好。给出了实验结果并进行了讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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