Single Image Super Resolution with various prediction networks
The goal of single-image super-resolution (SISR) is to transform a low-resolution image into a high-resolution version, enhancing both its detail and quality. This process, called upscaling, increases the image’s spatial resolution while sharpening and clarifying its visual features. While the objective remains the same, the methods to achieve SISR can vary. In this post (Part 1), I’ll explore three different neural network-based SISR approaches: color prediction, residual prediction, and kernel prediction....