Single Image Dehazing Based on Adaptive Histogram Equalization and Linearization of Gamma Correction

An Improved DCP-Based Image Defogging Algorithm Combined with Adaptive Fusion Strategy

“…is section presents qualitative and quantitative comparisons of the proposed method with classic defogging works [13,14,22,37] on a set of well-known benchmark real-world fog images (they are characterized by large depth, large depth and sharp edge, and large sky region, respectively) and synthetic images where the ground truth solutions are known. All algorithms are implemented in the Anaconda navigator 1.9.12 environment on inkPad T460 (Core i7, 8 GB RAM, 250 GB SSD) PC.…”

“…e histogram equalization-based defogging algorithm [22,23] makes the number of pixels in each gray level of the foggy image equal by replacing the original randomly distributed histogram of the image with the one of equal probability distribution in each interval and which can increase the contrast. Wavelet transform-based defogging methods [24,25] obtain the defogged clear image by using the Mallat algorithm to decompose the image matrix and filtering noise signal according to the characteristics of wavelet decomposition coefficient.…”

“…Because the real-world images lack ground truth, we must use the blind/referenceless image quality assessment metrics. e NIQE [5] is a well-known metric. e NIQE metric was proposed by Mittal et al, and the metric is based the principle of the certain regular statistical properties of the natural image.…”

“…Image processing-based methods can be further divided into image enhancement and image restoration. Among them, image enhancement-based defogging algorithms [5][6][7] take no consideration for the image degradation model but increase the contrast to obtain the visual defogged effect, resulting in distortion of defogged clear images. On the contrary, image restoration-based methods [8][9][10][11][12][13] consider the degradation process of foggy images, so the defogged clear images restored by these methods are closer to the real scene.…”

A Single Image Dehazing Technique Using the Dual Transmission Maps Strategy and Gradient-Domain Guided Image Filtering

“…Due to the uncertainty of weather itself and more unknown variables dehazing single images has always been a difficult task [12] [13]. Dehazing methods are mainly divided into two types: enhancement-based [12] [13] [14] and restorationbased dehazing methods. The former approach, somehow, improves the quality of resultant images but loses details, especially near edges.…”