Block-based multi-scale haze image enhancement method for surveillance application

Abstract

Images captured in surveillance systems suffer from low contrast and faint color. Recently, plenty of dehazing algorithms have been proposed to enhance visibility and restore color. We present a new image enhancement algorithm based on multi-scale block-rooting processing. The basic idea is to apply the frequency domain image enhancement approach for different image block scales. The parameter of transform coefficient enhancement for every block is driven through optimization of measure of enhancement. The main idea is that enhancing the contrast of an image would create more high-frequency content in the enhanced image than the original image. To test the performance of the proposed algorithm, the public database O-HAZE is used.

Image haze removal using block-based multiscale enhancement method

“…The hazy images have been captured in presence of real haze, generated by professional haze machines, and O-HAZE contains 45 different outdoor scenes depicting the same visual content recorded in haze-free and hazy conditions, under the same illumination parameters. In our experiments, the results are compared with methods [15,16,19,26,27]. Figures 3 and 4 demonstrate the image dehazing results obtained by various algorithms, respectively: a) the original image; b) the hazed image; c) the dehazed image by the proposed method; d) the dehazed image by the method [15]; e) the dehazed image by the method [16]; f) the dehazed image by the method [19]; g) the dehazed image by the method [26]; h) the dehazed image by the method [27].…”

“…In our experiments, the results are compared with methods [15,16,19,26,27]. Figures 3 and 4 demonstrate the image dehazing results obtained by various algorithms, respectively: a) the original image; b) the hazed image; c) the dehazed image by the proposed method; d) the dehazed image by the method [15]; e) the dehazed image by the method [16]; f) the dehazed image by the method [19]; g) the dehazed image by the method [26]; h) the dehazed image by the method [27]. A method proposed in [19] based on a priori information about the dark channel, which improves the results because of a more accurate transmission estimate.…”

Block-based multi-scale image enhancement method for industrial inspection system

“…To provide a comparison of the proposed fog/haze image enhancement method the publicly available database O-Haze is used [25]. In our experiments, the results are compared with methods [26,27,28,29,18]. Figures 4 demonstrate the image dehazing results obtained by various algorithms, respectively: a) the original image; b) the hazed image; c) the dehazed image by the proposed method; d) the dehazed image by the method [26]; e) the dehazed image by the method [27]; f) the dehazed image by the method [28]; g) the dehazed image by the method [29]; h) the dehazed image by the method [18].…”

“…The proposed enhancement method combines the sequential application of gamma and alpha correction operations. Gamma correction has already been extensively studied for image enhancement problems [16]; also, various adaptive alpha rooting enhancement methods have been proposed [17,18] to refine the transmission map and correct contrast on a hazy image.…”

“…found in the following (fig. 2 The block diagram of the proposed algorithm is shown in Figure 3 and consists of the following steps [18]:…”