An Algorithm for Repairing Low-Quality Video Enhancement Techniques Based on Trained Filter

TL;DR

This paper proposes a trained filter-based algorithm to repair low-quality image enhancement modules without altering their internal structure, improving their practical usability.

Contribution

It introduces a novel trained filter approach specifically designed for repairing and improving existing image enhancement modules.

Findings

The algorithm effectively repairs low-quality enhancement modules.

Experimental results show significant improvement in image quality.

The method preserves the original module structure while enhancing performance.

Abstract

Multifarious image enhancement algorithms have been used in different applications. Still, some algorithms or modules are imperfect for practical use. When the image enhancement modules have been fixed or combined by a series of algorithms, we need to repair them as a whole part without changing the inside. This report aims to find an algorithm based on trained filters to repair low-quality image enhancement modules. A brief review on basic image enhancement techniques and pixel classification methods will be presented, and the procedure of trained filters will be described step by step. The experiments and result comparisons for this algorithm will be described in detail.