1. A method of rendering an output image on basis of an input image and a corresponding matrix of depth related data, the input image corresponding to a first viewpoint and the output image corresponding to a second viewpoint being different from the first viewpoint, the method comprising: computing edges, via an edge detection unit, in the matrix of depth related data, by computing only derivatives of the depth related data in a predetermined direction (X), the edges corresponding to edges between (i) an object in a foreground of the input image and (ii) a background of the input image; computing a measure of variation in pixel values of the input image, via a texture analyzing unit, in regions of the input image that form a pixel subset (S vp ) that depends on the second viewpoint corresponding to neighborhoods of selected ones of the edges in de-occlusion areas as a function of the second viewpoint, wherein the neighborhoods in the de-occlusion areas are located at a background side of the selected ones of the edges, and wherein the computed measure of variation is a texture measure (T vp ) that comprises an average horizontal color change in the input image from one pixel to the next in the predetermined direction (X), averaged over a corresponding region of the pixel subset (S vp ); and computing the output image, via scaling and rendering units, by shifting respective pixel values of the input image in the predetermined direction (X) on basis of scaled depth related data, wherein the scaled depth related data comprises depth related data having been scaled on basis of the computed measure of variation, further wherein scaling via the scaled depth related data is such that a relative large measure of variation in pixel values in the regions of the input image that form the pixel subset (S vp ) of corresponding neighborhoods of the select ones of the edges in the de-occlusion areas results in a relative large reduction of depth perception via a reduction in dynamic range of depth values in the scaled depth related data scaled on the basis of the computed measure of variation.