All-Inclusive Image Enhancement for Degraded Images Exhibiting Low-Frequency Corruption

Abstract

In this paper, a novel image enhancement method, called the all-inclusive image enhancement (AIIE), is proposed that can effectively enhance the degraded images for improving the visibility of image content. These imageries were acquired under various types of weather conditions such as haze, low-light, underwater, and sandstorm, etc. One commonality shared by this class of noise is that the resulted degradations on visual quality or visibility are caused by low-frequency interference. Existing image enhancement methods lack the ability to deal with all types of degradations from this class, while our proposed AIIE offers a unified treatment for them. To achieve this goal, a statistical property is obtained from the study of the discrete cosine transform (DCT) of 1,000 high- and 1000 low-quality images on their DCT domains. It shows that the normalized DCT coefficients (between 0 and 1) of high-quality images has about 95% fall in the interval [0, 0.2]; for low-quality images, almost all the coefficients are in the same interval. This fundamental property, called the DCT prior (DCT-P), is instrumental to the development of our AIIE algorithm proposed in this paper. Since the proposed DCT-P delineates the attributes of high- and low-quality images clearly, it becomes a highly effective ‘tool’ to convert low-quality images to its enhanced version. Extensive experimental results have clearly validated the superior performance of the AIIE conducted on different types of deteriorated images in terms of visual quality and efficiency as well as significant advantages on computational complexity, which is essential for real-time applications.