It seems intelligent enhancement of image detail is currently high on the agenda at Google. Recently the company brought its RAISR smart image upsampling to Android devices. Now, the Google Brain team has developed a system that uses neural networking to enhance detail in low-resolution images.
The system uses a two-step approach, with a conditioning network first attempting to map 8 prior network adds realistic detail to the final output image. It does so by learning what each pixel in a low-resolution image generally corresponds to in higher-res files.
As you can see, the system already works pretty well. In the series of samples above, the images on the left show the 64 pixel source images, while the ones in the middle show the output image that the Google Brain algorithm has produced from them. The images on the right show higher-resolution versions of the low-res source images for comparison. While the results are not perfect yet, they are certainly close enough to provide value in a variety of scenarios. Eventually we might even be able to extract high-resolution images from low-quality security-cam footage a la CSI.
2017-2-9 23:07
