Systems and methods regulating filter strength for temporal filtering

A system for regulating filter strength for temporal filtering, comprising:

• one or more image sensors;
• one or more processors;
• and
• one or more computer-readable recording media that store instructions that are executable by the one or more processors to configure the system to:
• capture an image frame of a real-world environment using the one or more image sensors;
• obtain a light level indicator indicating light level associated with the real-world environment;
• determine a filter weight by processing the light level indicator using a filter strength regulation module that implements a weight function generated via noise simulation, wherein the weight function defines a weight for each of a plurality of light level indicator values, wherein the weight for each particular light level indicator value of the plurality of light level indicator values is selected by:
• converting a target intensity value into a linear value;
• generating a plurality of images where each pixel comprises the linear value with simulated noise;
• for each potential weight value for the particular light level indicator value:
• generating a filtered image using the plurality of images as input;
• converting the filtered image into an intensity image;
• and
• determining noise characteristics of the intensity image;
• and
• defining the weight for the particular light level indicator value as the potential weight value that is associated with noise characteristics that approximate a target spatial noise setting;
• generate an output image by using at least the filter weight to filter a current frame with a previous frame;
• and
• present the output image on a display of the system.

A system for regulating filter strength for temporal filtering, comprising:

• one or more processors;
• and
• one or more computer-readable recording media that store instructions that are executable by the one or more processors to configure the system to:
• determine a motion compensation confidence indicator using a current image and a previous image;
• convert the motion compensation confidence indicator into a reliability value;
• determine a filter weight by processing the reliability value using a filter strength regulation module;
• and
• generate an output image by using at least the filter weight to filter a current frame with a previous frame.