Published Paper Details:

Real-time image processing is usually associated with the problems of system slowness and image quality decline, especially in low-light conditions. This work proposes a novel approach utilizing a three-dimensional channel flexing mechanism for brightness enhancement and noise reduction. The channel flexing mechanism operates along three dimensions under a multistacked structure with the K-means clustering technique to enhance image brightness and minimize noise. The separation of the illuminated and dark images facilitates conversion to target pixels. The presented three-dimensional channel flexing technique employs triggers for dynamically swapping between the Red, Blue, and Green channels to avoid introducing luminous regions into oversaturation. The energy is allocated uniformly among respective clusters for higher PSNR. The standard assessment of the processed images has been done based on three major parameters: PSNR, SSIM, and MAE. The evaluation metrics show that this technique provides good visual quality and computation time, proving its adequacy for real-time image enhancement. The results imply that this strategy is particularly suitable for real-time visual enhancement in computer vision systems.