scholarly journals Polarimetric Dehazing Method Based on Image Fusion and Adaptive Adjustment Algorithm

2021 ◽  
Vol 11 (21) ◽  
pp. 10040
Author(s):  
Yu Lei ◽  
Bing Lei ◽  
Yubo Cai ◽  
Chao Gao ◽  
Fujie Wang
Keyword(s):  
Image Fusion ◽  
Degree Of Polarization ◽  
Fusion Technique ◽  
Low Degree ◽  
Low Pass ◽  
Adaptive Adjustment ◽  
Image Fusion Technique ◽  
Focus Plane ◽  
Polarization Camera

To improve the robustness of current polarimetric dehazing scheme in the condition of low degree of polarization, we report a polarimetric dehazing method based on the image fusion technique and adaptive adjustment algorithm which can operate well in many different conditions. A splitting focus plane linear polarization camera was employed to grab the images of four different polarization directions, and the haze was separated from the hazy images by low-pass filtering roughly. Then the image fusion technique was used to optimize the method of estimating the transmittance map. To improve the quality of the dehazed images, an adaptive adjustment algorithm was introduced to adjust the illumination distribution of the dehazed images. The outdoor experiments have been implemented and the results indicated that the presented method could restore the target information obviously, and both the visual effect and quantitative evaluation have been enhanced.

scholarly journals Underwater Image Restoration Based on Image Fusion

2020 ◽  
Vol 9 (2) ◽  
pp. 621-626
Keyword(s):  
Laplace Transform ◽  
Image Fusion ◽  
Image Restoration ◽  
Essential Feature ◽  
Fusion Technique ◽  
Scattering Of Light ◽  
Multi Scale ◽  
Underwater Image ◽  
Image Fusion Technique

The haziness in underwater images occurs due to two major phenomena namely absorption and scattering of light. Hence, we have proposed an image fusion-based approach to improve the visibility of images obtained underwater. The proposed method uses a single hazy image. Initially the colour corrected and contrast improved versions of the image are obtained. Further, Laplace transform is applied which is followed by replication and saliency mapping on each of the derived images. Multi-scale image fusion technique has been used to combine the inputs. This enables each of the fused images to contribute the most essential feature to obtain the resultant image. Thus, the proposed method significantly restores the quality of the input distorted images.

scholarly journals Image Fusion Technique Based on Hybrid Whale Optimization Algorithm Simulated Annealing (hWOA-SA)

2019 ◽  
Vol 8 (11) ◽  
pp. 19-24
Keyword(s):  
Simulated Annealing ◽  
Image Fusion ◽  
Optimization Algorithm ◽  
Curvelet Transform ◽  
Whale Optimization Algorithm ◽  
Fusion Technique ◽  
Whale Optimization ◽  
Image Fusion Technique ◽  
Combined Algorithm

Curvelet transform is a multiscale directional transformer, which allows optimal non-adaptive sparse representation of object with edge. In this paper, a new image fusion technique has been developed by combination of whale optimization algorithm (WOA) and simulated annealing (SA) along with curvelet transform. The resulting combined algorithm is abbreviated as hybrid whale optimization algorithm with simulated annealing. Initially, hWOA-SA has been applied to enhancing the quality of image using de-noising scheme. Afterwards, the curvelet transform has been employed to carry out the fusion of images. In terms of PSNR, the curvelet transform exhibits the better performance. The effectiveness and validation of the proposed scheme has been carried-out using quality matrices. The performance analysis is carried out after checking the effectiveness of proposed approach by evaluating the various parameters such as: RSME, PFE, MAE, CORR, SNR, PSNR, MI, UQI and SSIM and compared with numerous techniques. Simulation results obtained from proposed hWOA-SA based image fusion are very competitive and better than other image fusion technique available in the literature.

Sign in / Sign up

Export Citation Format

Share Document