Systems and methods for perceptual quality-driven adaptive quantization in neural network data compression with dynamic feedback control

A computer system comprising:

• a hardware memory, wherein the computer system is configured to execute software instructions stored on nontransitory machine-readable storage media that:
• preprocess raw data to generate input data;
• analyze content characteristics of the input data to determine initial quantization parameters;
• perform content-aware quantization on the input data using the determined quantization parameters;
• perform a discrete cosine transform operation on the quantized input data to create a plurality of subbands;
• compress the plurality of subbands using an encoder within a multi-layer autoencoder to generate compressed data;
• perform at least one additional compression pass on the plurality of subbands using the encoder within the multi-layer autoencoder to generate at least one additional compressed bitstream, and multiplex the compressed data and the at least one additional compressed bitstream into a combined bitstream;
• collect quality metrics from the combined bitstream, the quality metrics comprising at least a perceptual quality score and a compression measure of the compressed data;
• store the quality metrics in a quality history database, wherein the quality history database may be accessed during a future compression of a second plurality of subbands;
• generate parameter adjustment signals, wherein the parameter adjustment signals are based on the collected quality metrics and a quality assessment analysis;
• modify the quantization parameters based on the parameter adjustment signals to create optimized quantization parameters for subsequent compression operations while implementing gradual parameter updates to maintain stability;
• decompress the combined bitstream using a decoder within the multi-layer autoencoder to obtain reduced output data;
• and
• process the reduced output data through a context recovery network to recover information lost in compression, thereby generating restored output data.