Towards Super Resolution

CIFAR-10 image (32x32x3) very low resolution
500x500, but very poor quality
  1. Assemble a dataset of high-resolution images
  2. Copy them into another array, (this will be the x train data)
  3. Downsample these x input images to the desired low-resolution size ex: 600 x 600 → 200 x 200
  4. Use bicubic interpolation to upsample the images back to 600 x 600
  5. Now train the Convolutional Network given inputs of upsampled low-resolution images and outputs of the original high-resolution images.
High-Resolution Deer Image, (In Heavy Contrast with the Cifar-10 image above)


Connor Shorten is a Computer Science student at Florida Atlantic University. Research interests in deep learning and software engineering.



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