Patent ID: 11909975
Assignee: TENCENT AMERICA LLC
Field: Audio-visual technology (Electrical engineering)
Classification: CPC H  G | IPC G  H

Claim 15:
16. A non-transitory computer readable medium storing instructions that, when executed by at least one processor for end-to-end neural image compression using dependent scalar quantization with substitution, cause the at least one processor to:
receive an input image;
determine a substitute image based on the input image using a neural network based substitute feature generator;
compress the substitute image;
quantize the compressed substitute image to obtain a quantized representation of the input image with higher compression performance by using a first dependent scalar quantizer, and
entropy encode the substitute image using a neural network based encoder to generate a compressed representation of the quantized representation,
wherein a compression quality loss associated with the compressed substitute image is less than a compression quality loss associated with a compressed input image, and
wherein one or more neural network model used in the method may be jointly optimized to minimize an overall rate-distortion loss.