摘要:
A method for enhancement of edges in image frames using depth information, includes receiving a color image frame and a depth map frame (510). The method also includes generating a sharpness mask to control the application of image sharpening to the color pixels (520). The sharpness mask is based on the value of depth pixels corresponding to the color pixels, and on properties of the depth camera (104) that generated the color image frame, including depth of field, focal distance, and hyperfocal distance. The method further includes calculating sharpness strength for the color pixels (530). The sharpness strength is proportional to the value of the depth pixel corresponding to the color pixel. The method further includes applying a sharpening filter to the color image frame to enhance edge image features (540). The sharpening filter is based on the sharpness mask and the sharpness strength.
摘要:
Various embodiments are provided which relate to the field of image signal processing, specifically relating to the generation of a depth-view image of a scene from a set of input images of a scene taken at different cameras of a multi-view imaging system. A method comprises obtaining a frame of an image of a scene and a frame of a depth map regarding the frame of the image. A minimum depth and a maximum depth of the scene and a number of depth layers for the depth map are determined. Pixels of the image are projected to the depth layers to obtain projected pixels on the depth layers; and cost values for the projected pixels are determined. The cost values are filtered and a filtered cost value is selected from a layer to obtain a depth value of a pixel of an estimated depth map.
摘要:
The invention relates to an image processing method for detail enhancement and noise reduction, in which the following steps are included: (a) an original image is created, (b) an information measure is calculated on the basis of the original image, (c) a weighting measure is calculated on the basis of the information measure, (d) the original image is low-pass filtered with a low-pass filter to form a low-pass filtered image, (e) a high-pass filtered image is calculated by subtracting the low-pass filtered image from the original image, (f) a detail-enhanced and noise-reduced image is obtained by a high-pass image scaled with the weighting measure being added to the low-pass image.
摘要:
A system and method for enhancing the detail edges and transitions in an input video signal. This enhancement may be accomplished by enhancing small detail edges before up-scaling and enhancing large amplitude transitions after up-scaling. For example, detail edge enhancement (detail EE) may be used to enhance the fine details of an input video signal. An edge map may be used to prevent enhancing the large edges and accompanying mosquito noise with the detail enhancement. Noise may additionally be removed from the signal. After the fine details are enhanced, the signal may be up-scaled. Luminance transition improvement (LTI) or chrominance transition improvement (CTI) may be used to enhance the large transitions of the input video signal post scaler.
摘要:
Blurred image data is sharpened by converting three channels of RGB data into a single channel of intensity data, processing the intensity data to generate integral image data, applying a variable size filter to the integral image data to generate box- filtered data, calculating a gain factor for each pixel position in dependence upon the box- filtered data, the intensity data and the size of the filter used for that pixel position, and multiplying the original RGB data of each pixel by the gain factor for that pixel to generate sharpened RGB data. The size of the filter is selected at each pixel position in dependence upon an estimate of the local amount of blur. In this way, as the amount of blur changes, the filter size changes appropriately. By processing the integral image data to generate box- filtered data, a constant number of processing operations are required for image sharpening irrespective of the size of filter that is used.
摘要:
Using Identification of their sizes and positions, objects may be attenuated or removed from images. This may involve the use of various filtering operations and may further include coordinate transformations prior to and/or after the filtering. The filtered objects may then be subtracted from the image.
摘要:
The invention relates to a method, a device, an image quality evaluation module and a computer program product for determining the quality of an image. In an input image, at least one color component is iteratively restored with a deblur parameter, which deblur parameter is increased at each iteration. The iteration is stopped when an overshooting in the final image exceeds a predetermined value. After the iteration has been stopped, a number of iterations is defined and the quality of the image is determined according to the number of iterations.
摘要:
Verfahren und Einrichtung zur Dynamikkompression in Bildern oder Signalreihen, welche durch einzelne Amplitudenwerte repräsentiert sind, wobei Eingangsamplitudenwerte EA der Bilder oder Signalreihen einer lokalen räumlichen Amplitudenmittelung unterzogen und lokal räumlich gemittelte Eingangsamplitudenwerte erzeugt werden (20), aus Differenzen der Eingangsamplitudenwerte EA und der lokal räumlich gemittelten Eingangsamplitudenwerte Differenzfunktionswerte gebildet (30), und aus den gebildeten Differenzfunktionswerten Ausgang- samplitdenwerte AA der Bilder oder Signalreihen erzeugt werden (50, 60). Erfindungsgemäß ist es vorgesehen, dass bei der Bildung der Differenzfunktionswerte den aus den Eingangsamplitudenwerten EA und den lokal räumlich gemittelten Eingangsamplitdenwerten gebildeten Differenzen zusätzlich Differenzwerte überlagert werden (40), welche aus den Eingangsamplitudenwerten EA und einem vorgegebenen Bezugswert GA gebildet werden.
摘要:
Reduction of noise in digitized multi-spectral images is provided by filtering based on vector values rather than independent scalar values. Vector values to a pixel with two or more values. For this method, a metric is defined for pixel vector magnitude. A sliding processingkernel is also defined, with a specified shape, a specified numer of pixels to be included in the kernel, and a specified value contrast threshold to avoid distorting edges and fine details. The metric and kernel are used to select pixels for computing filtering of the center pixel in a kernel. A statistical measurement is computed, for example by mean averaging the specified pixels, and the resulting value is made the value of the center pixel of the kernel. The filtering process is applied throughout the image by making each pixel the center of a processing kernel.