Image scaling curve generation.

The present invention relates to a method of generating an image scaling curve, where local saliency is detected in a received image. The detected local saliency is then accumulated in the first direction. A final scaling curve is derived from the detected local saliency and the image is then possibly rescaled in a second direction by using the derived scaling curve, wherein the second direction is substantially orthogonal to the first direction

Image scaling curve generation

The present invention relates to a method of generating an image scaling curve, where local saliency is detected in a received image. The detected local saliency is then accumulated in the first direction. A final scaling curve is derived from the detected local saliency and the image is then possibly rescaled in a second direction by using the derived scaling curve, wherein the second direction is substantially orthogonal to the first direction

Method and apparatus for modifying an imgage by using a saliency map based on color frequency

A method for modifying an image being defined by a matrix of pixels comprises: DEG calculating (1) a color frequency distribution of the matrix of pixels; DEG defining (3) for each pixel an energy value as a weighted function of the color frequency of the pixel, so as to define an image saliency map; DEG transforming (5) the image, said transformation being based on the pixel energy values. A computer software product to apply the method, an apparatus and a TV set are also disclosed

Apparatuses and methods for improved encoding of images

To allow better quality rendering of video on any display, a method is proposed of encoding, in addition to video data (VID), additional data (DD) comprising at least one change time instant (TMA-1) indicating a change in time of a characteristic luminance (CHRLUM) of the video data, which characteristic luminance summarizes the set of luminances of pixels in an image of the video data, the method comprising: -generating on the basis of the video data (VID) descriptive data (DED) regarding the characteristic luminance variation of the video, the descriptive data comprising at least one change time instant (TMA-1), and-encoding and outputting the descriptive data (DED) as additional data (DD)

Additional

Adaptive online learning based tissu