Abstract: A method for using a computing device for modifying a lower dynamic range image to a higher dynamic range image is described. According to the method, a lower dynamic range image including a plurality of pixels is analyzed by estimating a dark channel of the plurality of pixels of the lower dynamic range image. A histogram of the dark channel is analyzed by determining the brightest peak and a local minima of the histogram. Using the local minima of the histogram as a threshold for specular highlight determination, a binary mask for specular highlight determination is computed. A final mask is created by multiplying the luminance value of the lower dynamic range image with the binary mask. The final mask is then used to determine the higher dynamic range image. A system for converting a lower dynamic range image to a higher dynamic range image displays the higher dynamic range image on a higher dynamic range display.

Abstract: A method for image enhancement may include selecting a plurality of patches of an image and determining at least one dimensionally reduced feature for each of the plurality of patches. The system may further determine a generally closest cluster from a set of clusters for each of the dimensionally reduced features and select a corresponding set of regression coefficients for each of the set of generally closest cluster. The system may also apply the selected set of regression coefficients to a corresponding patch to enhance the image.

Abstract: A system for determining a high resolution output image that includes receiving a low resolution image and determining an intermediate high resolution image. The system detects semantic features based upon the input image and selects corresponding semantic components from a database based upon the detected semantic features. The first intermediate high resolution image is modified based upon information from the corresponding semantic components to determine the high resolution output image.

Abstract: A system for enhancing an image includes a cadence detection process that detects a cadence of a series of frames and a scene cut detection process that detects a scene cut of the series of frames. The system also includes a noise monitoring process that detects noise in the series of frames based upon the cadence detection process. The process further includes a temporal filter temporally filtering the series of frames wherein the temporal filtering is modified based upon the scene cut detection process and the noise monitoring process. The system also includes a spatial noise reduction process reducing spatial noise in the series of frames wherein the reducing spatial noise is modified based upon the modified temporally filtered frames and the noise monitoring process.

Abstract: A system for determining a high resolution output image that includes receiving a low resolution image and determining an intermediate high resolution image. The system detects semantic features based upon the input image and selects corresponding semantic components from a database based upon the detected semantic features. The first intermediate high resolution image is modified based upon information from the corresponding semantic components to determine the high resolution output image.

Abstract: Aspects of the present invention are related to systems and methods for detection and estimation of mosquito noise in an image or in a video sequence. A mosquito-noise estimate, at a pixel location, may be computed based on an image ring parameter, a statistical value of noise estimates in a first region associated with the pixel location, a maximum activity value in a second region associated with the pixel location and a noise estimate at the pixel location.

Abstract: A system for determining a high resolution image includes receiving a low resolution image and determining a vector of a patch of the low resolution image based upon a low resolution dictionary. The system includes determining a high resolution patch based upon a high resolution dictionary and the vector and determining the high resolution image based upon the high resolution patch.