We introduce a general framework for end-to-end optimization of the rate-distortion performance of nonlinear transform codes assuming scalar quantization. The proposed 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 optimize a code built from a linear transform followed by a form of multi-dimensional gain control. Distortion is measured with a state-of-the-art perceptual metric. The code, optimized over a large database of images, offers substantial improvements in bitrate and perceptual appearance over fixed (DCT) codes, as well as over linear transform codes optimized for mean squared error.

本文介绍了一种通用的框架，用于端到端优化非线性变换编码的速率失真性能，可以使用任何可微分的分析和综合变换与任何可微分的感知度量相结合，例如使用多维本地增益控制构建的线性变换后的编码，通过现代感知度量对失真进行测量以优化大型图像数据库上的编码，相较于固定的（DCT）编码以及为均方误差而优化的线性变换编码，该表示提供了显着的比特率和感知外观的改进。

面向感知质量的非线性变换编码的端到端优化