Abstract: A computer-implemented method that includes segmenting a training image into training image patches, where each training image patch is represented by a linear combination of dictionary image patches from an image dictionary, and each dictionary image patch has a sparse representation coefficient. The method includes segmenting a stylized training image into stylized training image patches, where each stylized training image patch is represented by a linear combination of stylized dictionary image patches from a stylized image dictionary, and each stylized dictionary image patch has a sparse representation coefficient. The method also includes training the image dictionary with the training image patches and the stylized image dictionary with the stylized training image patches in a substantially simultaneous manner. The sparse representation coefficient for each training image patch is substantially similar to the sparse representation coefficient for the corresponding stylized training image patch.

Abstract: The present invention provides two-scale tone management of an input image. A method of providing two-scale tone management contains the steps of: separating the input image into a base layer and a detail layer; separating a model image into a base layer and a detail layer; analyzing the input image globally for global contrast; analyzing the input image locally for local contrast; and performing detail preservation of the input image. A system contains a memory and a processor, where the processor is configured by the memory to perform the steps of: separating the input image into a base layer and a detail layer; separating a model image into a base layer and a detail layer; analyzing the input image globally for global contrast; analyzing the input image locally for local contrast; and performing detail preservation of the input image.

Abstract: The present invention provides gradient preservation of an input image. A method of providing gradient preservation of an input image, comprises the steps of: computing gradient fields of the input image; computing gradient fields of a remapped image, wherein the remapped image is the input image remapped; comparing a gradient of the remapped image to a predefined range of acceptable values, wherein the acceptable values depend on the input gradient; changing values of the gradient of the remapped image if the values of the gradient of the remapped image are not within the predefined range of acceptable values depending on the input gradient, resulting in x and y components of a modified gradient; and reconstructing the input image using the x and y components of the modified gradient.