Systems and methods for dynamic range compression in multi-frame processing

An electronic device comprising:

• at least one processing device configured to:
• obtain a high dynamic range (HDR) input Bayer image;
• generate a plurality of synthesized images at different exposure levels based on the input Bayer image;
• fuse the synthesized images to generate a fused image;
• generate a gain map based on the fused image;
• apply a gain based on the gain map to the input Bayer image;
• and
• output a displayable range image based on the applied gain, wherein the applied gain is determined as a weighted average of three color planes;
• wherein a gain value applied to each sample in the displayable range image comprises an interpolated value based on the gain map.

A non-transitory machine-readable medium containing instructions that when executed cause at least one processor of an electronic device to:

• obtain a high dynamic range (HDR) input Bayer image;
• convert the input Bayer image into a Luma domain image;
• generate a plurality of synthesized images at different exposure levels based on the Luma domain image;
• fuse the synthesized images to generate a fused image;
• generate a gain map based on the fused image;
• and
• apply a gain based on the gain map to the input Bayer image;
• wherein the instructions that when executed cause the at least one processor to generate the plurality of synthesized images comprise instructions that when executed cause the at least one processor to:
• generate a first lookup table (LUT) based on a compression LUT and a contrast LUT, the compression LUT and the contrast LUT based on the input Bayer image;
• generate a second LUT based on the first LUT;
• and
• apply the first LUT and the second LUT to the Luma domain image.

A non-transitory machine-readable medium containing instructions that when executed cause at least one processor of an electronic device to:

• obtain a high dynamic range (HDR) input Bayer image;
• generate a plurality of synthesized images at different exposure levels based on the input Bayer image;
• fuse the synthesized images to generate a fused image;
• generate a gain map based on the fused image;
• and
• apply a gain based on the gain map to the input Bayer image;
• wherein the instructions that when executed cause the at least one processor to generate the plurality of synthesized images comprise instructions that when executed cause the at least one processor to generate YUV domain images based on the input Bayer image;
• and
• wherein the instructions that when executed cause the at least one processor to generate the YUV domain images comprise instructions that when executed cause the at least one processor to:
• determine first, second, and third scales based on scene statistics;
• generate first, second, and third exposure images based on the first, second, and third scales, respectively;
• and
• clip the first, second, and third exposure images into first, second, and third Bayer images, respectively.