Training image signal processors using intermediate loss functions

At least one memory device comprising computer readable instructions that, when executed, cause processor circuitry to at least:

• apply a sensor image to an image signal processor to generate a reconstructed image;
• implement a first loss function based on comparison an intermediate layer of a first computer vision network with a corresponding intermediate layer of a second computer vision network, the first computer vision network to process the reconstructed image, the second computer vision network to process an input image associated with the sensor image;
• iteratively determine values of a second loss function by combining weighted values of the first loss function and a third loss function at successive training iterations, the third loss function based on one or more results output from the first computer vision network, the instructions to cause the processor circuitry to weight a value of the first loss function by a first weight at a first training iteration and weight a value of the third loss function by a second weight at the first training iteration;
• and
• modify a parameter of the image signal processor based on at least one of the first loss function or the second loss function.

A method comprising:

• generating, with an image signal processor, a reconstructed image from a sensor image;
• determining, by executing an instruction with processor circuitry, values of a first loss function at successive training iterations based on comparison of an intermediate layer of a first computer vision network with a corresponding intermediate layer of a second computer vision network, the first computer vision network to process the reconstructed image, the second computer vision network to process an input image associated with the sensor image;
• iteratively determining, by executing an instruction with the processor circuitry, values of a second loss function by combining weighted values of the first loss function and a third loss function at successive training iterations, the third loss function based on one or more results output from the first computer vision network, a value of the first loss function weighted by a first weight at a first training iteration and a value of the third loss function weighted by a second weight at the first training iteration;
• and
• modifying, by executing an instruction with the processor circuitry, a parameter of the image signal processor based on at least one of the first loss function or the second loss function.