The University of North Carolina at Chapel Hill

Chong Shao

Russell Morton Taylor, Ii

Ketan Dasharath Mayer-Patel

Zhigang Zhong

According to one exemplary method, the method includes classifying image pixels in each video image of a series of video images as either foreground or background. The method also includes replacing each pixel classified as background with a time-averaged value of pixel intensity for that pixel. The method further includes compressing the video images using a compression algorithm.

Methods, systems, and computer readable media for compressing video images

Methods, systems, and non-transitory computer readable media for reconstructing electronic images using blurring and noise-enhanced pixel intensity resampling are disclosed. One method includes, at an image reconstructor including at least one processor, receiving an image compressed using an image compression algorithm. The method further includes decompressing the image using an image decompression algorithm. The method further includes modifying pixel intensities in the image by blurring and/or resampling the pixel intensities according to a noise distribution generated by the reconstructor without receiving a noise estimate from an image compressor. The method further includes outputting the image with the modified pixel intensities.

Growing community of inventors

Chapel Hill, NC, United States of America

Chong Shao