Research on Film and Television Image Enhancement Algorithm Based on Adaptive Color Compensation

The complexity of filming environments and various interference factors lead to issues such as color distortion, low visibility, and blurred details in many images, severely affecting applications based on visual technology. To extract useful information from images, enhancement and restoration are necessary to improve image quality. Therefore, this paper proposes an image enhancement algorithm based on adaptive color compensation and super-resolution reconstruction, specifically targeting film and television images that face both color distortion and low resolution. An adaptive color compensation method is designed to supplement pixels in color-distorted images, taking into account the characteristics of image attenuation. A gamma correction method is employed to suppress and enhance overly bright and dark areas of the image. A deep coupling feedback network is designed to fully integrate the overly bright and dark regions through the collaboration of various modules, while also improving image resolution. Additionally, a hybrid loss function is designed to supervise network training. Comprehensive comparative experiments were conducted on public datasets and synthetic datasets, and the results indicate that this method further improves the issue of low image resolution in film and television image enhancement, resulting in more realistic color tones and clearer textures.