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

Claim 9:
10. An apparatus for end-to-end neural image compression using dependent scalar quantization with substitution, the apparatus comprising:
at least one memory configured to store program code; and
at least one processor configured to read the program code and operate as instructed by the program code, the program code comprising:
first receiving code configured to cause the at least one processor to receive an input image;
first determining code configured to cause the at least one processor to determine a substitute image based on the input image using a neural network based substitute feature generator;
compressing code configured to cause the at least one processor to compress the substitute image;
quantizing code configured to cause the at least one processor to 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
first generating code configured to cause the at least one processor to 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 models used in the method may be jointly optimized to minimize an overall rate-distortion loss.