Super Resolution: Adobe Photoshop versus Leading Deep Neural Networks.¶

Super Resolution is a technique that enhances the quality of an image by increasing its apparent resolution, effectively imagining the detail present in a higher-resolution version. Traditional methods like bicubic interpolation often result in blurred images when upscaling. Recent advancements have introduced more sophisticated approaches, including Adobe Camera Raw's Super Resolution and deep learning models such as the Information Distillation Network (IDN).

Adobe's Super Resolution, integrated into Adobe Camera Raw and Photoshop, utilizes an advanced machine learning model trained on millions of photos. This feature allows users to enhance image resolution with a single click, delivering impressive results in both performance and speed. While Adobe has not disclosed detailed technical specifics, the algorithm's effectiveness suggests the use of deep neural network techniques.

The Information Distillation Network (IDN) represents a deep convolutional neural network architecture developed by researchers Zheng Hui, Xiumei Wang, and Xinbo Gao. IDN is recognized for its fast and accurate single-image super-resolution capabilities, generalizing well across various images. Unlike earlier models that focused on small 'postage stamp' images, IDN has been evaluated on relatively high-resolution images, demonstrating its applicability to more substantial image enhancement tasks.

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Super Resolution: Adobe Photoshop versus Leading Deep Neural Networks