视觉机制引导的非均匀光照图像二次曝光

针对非均匀光照图像不能满足"视觉匹配"的问题, 依据人眼视觉机制提出了非均匀光照图像二次曝光算法. 首先, 融合退化过程模拟模型(Degradation process simulation model, DPSM)和Retinex模型得到了非均匀光照图像的成像模型, 利用修正的变分Retinex求解方法,获取乘性光照图像; 在人眼视觉阈值性的引导下去除加性光照图像, 获取反射图像; 依据视觉感光适应性对乘性光照图像进行动态范围调整, 并同反射图像相乘获取全局增强结果; 将全局增强结果同原始图像融合, 并对低照度区域进行颜色校正, 获取"视觉匹配"结果. 实验证明本文算法的场景再现结果可以较好地满足"视觉匹配", 性能达到或者超越了现有算法.

Non-uniform Lightness Image Repeated Exposure Directed by Visual Mechanism

Non-uniform lightness image could not satisfy "visual matching". To solve the problem, a novel method called "non-uniform lightness image repeated exposures" is proposed in this paper, which is based on human visual mechanism. Firstly, by combining degradation process simulation model (DPSM) and Retinex model, we get a non-uniform lightness image formation model which the proposed method is based on, and the multiplicative lightness image is obtained through using modified variational Retinex solution on this model. Then additive lightness image is eliminated and an reflectance image is obtained through simulating the human visual threshold mechanism. Photoreceptor adaptation is adapted to upgrade the brightness and compress the dynamic of multiplicative lightness image, and the global enhancement result is obtained by multiplying it by the reflectance image. Finally, the global enhancement result and the original image are fused together, then the "visual matching" image is obtained after color adjusting on low illumination area. Experimental results indicate that the proposed algorithm could get "visual matching" image and its performance could achieve or exceed the existing algorithms.