Abstract: The present invention relates to a method for processing digital image data (ID), wherein the process of multi rate, multi resolution and/or multi scale signal processing is involved in order to realize a respective multi rate, multi resolution and/or multi scale sharpness enhancement with respect to said image data (ID).

Abstract: The present invention relates to a method for classifying a signal (S). An intermediate signal (IS) is decimated in order to obtain a processed signal (PS) as a new intermediate signal (IS). A processed signal (PS) is compared with respect to the signal (S) to be classified to thereby generate comparison data (CompDAT). Based on the comparison data (CompDAT) said signal (S) to be classified is classified, thereby classification data (ClassDAT) are generated.

Abstract: A method for pre-processing image data is proposed, wherein a image (PI) is pre-distorted in order to compensate a distortion created by a display process. According to the inventive method an additional memory is used wherein said image (PI), a pre-distorted image (PPI), parts thereof, in particular extra pixels thereof, are stored in said additional memory.

Abstract: An adaptive histogram equalization method is introduced which allows the histogram equalization amount to automatically adapt to the original image contrasts, which can be measured from the originals. Contrast over-enhancement is avoided by limiting the spatial frequency response of the histogram. Besides that, methods to remedy the brightness change problem encountered by histogram equalization are described.

Abstract: A method for pre-processing image data is suggested wherein a step of pre-processing (S2) received primary image data (PID) is performed by applying a pre-distortion operation (PDO) to said primary image data (PID) so as to obtain secondary image data (SID). Said pre-distortion operation (PDO) is chosen to correspond to an inverse (IDO) of a distortion operation (DO) of a display process (S4) to be used for displaying said secondary image data (SID) to therefore compensate an non-uniformity of said image generation process (S4) with respect to image data without pre-distortion. The non-uniformity correction can be included within or be performed together with an image processing function.

Abstract: An adaptive histogram equalization method is introduced which allows the histogram equalization amount to automatically adapt to the original image contrasts, which can be measured from the originals. Contrast over-enhancement is avoided by limiting the spatial frequency response of the histogram. Besides that, methods to remedy the brightness change problem encountered by histogram equalization are described.