Image Processing Reference
In-Depth Information
Night color image
enhancement via statistical
law and retinex
Huaxia Zhao; Chuangbai Xiao; Hongyu Zhao College of Computer Science and Technology, Beijing University of Technology,
Beijing, China
Due to the uneven distribution of light at night, the quality of the night color image is usually unsatis-
factory. To solve this problem, in this article, we propose a new statistical method based on the retinex.
The algorithm analyzes the transformation relationship between the nightime image and illumination
image by the algorithm of Michael Elad and MSRCR algorithm. Through this transformation, we can ac-
curately and quickly get the illumination image. Then, we can get the resulting image successfully based
on the retinex. Our algorithm can greatly enhance the image contrast and brightness, recover image de-
tails, eliminate the “halo effect” efficiently, and accelerate the computational speed remarkably. Experi-
ments on diferent nightime images demonstrate the efectiveness of our approach.
Statistical law
Image enhancement
Night color image
Illumination image
1 Introduction
The night color image enhancement is of great importance in both the computational photo-
graphy and computer vision. First, it can effectively increase the visibility and surrealism of
the scene. Second, artificial illumination light distributes unevenly at night leading to weak-
ening the quality of monitoring photos and increasing the difficulty of surveillance. Thus, the
night color image enhancement can promote the video surveillance. Last, the input images of
most computer vision algorithms (e.g., the photometric analysis algorithm) are daytime images.
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