Image processing is a crucial aspect of computer vision, with applications in various fields such as medical imaging, object detection, and image enhancement. Traditional image processing techniques often rely on hand-crafted features or convolutional neural networks (CNNs) that process images in a holistic manner. However, these approaches can be limited by their inability to effectively capture local patterns and textures in images. To address this limitation, a novel approach called Patch-Driven-Net has been proposed.