End-to-end optimization of nonlinear transform codes for perceptual quality

Understand

We introduce a general framework for end-to-end optimization of the rate--distortion performance of nonlinear transform codes assuming scalar quantization.

• The framework can be used to optimize any differentiable pair of analysis and synthesis transforms in combination with any differentiable perceptual metric.
• As an example, we consider a code built from a linear transform followed by a form of multi-dimensional local gain control.
• Distortion is measured with a state-of-the-art perceptual metric.