Does Haze Removal Help CNN-based Image Classification?

Understand

Hazy images are common in real scenarios and many dehazing methods have been developed to automatically remove the haze from images.

• Typically, the goal of image dehazing is to produce clearer images from which human vision can better identify the object and structural details present in the images.
• When the ground-truth haze-free image is available for a hazy image, quantitative evaluation of image dehazing is usually based on objective metrics, such as Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity (SSIM).
• However, in many applications, large-scale images are collected not for visual examination by human.