Park Chae Rim, Lee Kwang Ill, Cho Seok Je

KIPS Transactions on Software and Data Engineering, Vol. 12, No. 2, pp. 83-90, Feb. 2023
https://doi.org/10.3745/KTSDE.2023.12.2.83,   PDF Download:
Keywords: Deblurring, Attention, Retinex, Color Constancy, computer vision
Abstract

Blurred image is an important factor in lowering image recognition rates in Computer vision. This mainly occurs when the camera is unstablely out of focus or the object in the scene moves quickly during the exposure time. Blurred images greatly degrade visual quality, weakening visibility, and this phenomenon occurs frequently despite the continuous development digital camera technology. In this paper, it replace the modified building module based on the Deep multi-patch neural network designed with convolution neural networks to capture details of input images and Attention techniques to focus on objects in blurred images in many ways and strengthen the image. It measures and assigns each weight at different scales to differentiate the blurring of change and restores from rough to fine levels of the image to adjust both global and local region sequentially. Through this method, it show excellent results that recover degraded image quality, extract efficient object detection and features, and complement color constancy.

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