Abstract: A method for identifying state of macro block of de-interlacing computing and an image processing apparatus are provided, the method is as follows. A video frame is divided into a plurality of regions, where each of the regions includes a plurality of macro blocks. Then, a basic threshold corresponding to each of the regions is provided according to a position of each of the regions in the video frame, and a first macro block is identified to be a first type macro block or a second type macro block according to the basic threshold corresponding to one of the regions where the first macro block of the macro blocks locates. Then, a corresponding de-interlacing computing step is performed on the first macro block according to an result that the first macro block is identified as the first type macro block or the second type macro block.

Abstract: Current output pictures of video data are generated utilizing a motion compensated (MC) blended picture and a corresponding non-MC blended picture of the video data. Windows of picture data from a first picture and MC windows of picture data from a MC previously output picture may be partitioned. The partitioned widows are compared and the first picture is blended with the MC previously output picture based on the comparison to, for example, reduce noise and prevent motion trail artifacts. Non-MC windows of picture data from a MC or non-MC previously output picture may be partitioned and compared with the windows of picture data from the first picture. The first picture may be blended with the MC or non-MC previously output picture based on the comparison to reduce motion trail artifacts. A blending factor is determined and utilized to blend the blended pictures to reduce noise and prevent motion artifacts.

Abstract: In an embodiment, there is provided a video processing component comprising a compensation engine configured to generate pixels of a first video frame from a second video frame based at least in part on specified pixel motion; and an access buffer configured to store pixel data corresponding to pixels of the second video frame for reference by the compensation engine, wherein the pixel data is stored by the access buffer at different vertical resolutions depending on vertical distances of the pixels corresponding to the pixel data from a target pixel that is indicated by the compensation engine.

Abstract: An image processing system for processing a target pixel to be processed, which target pixel corresponds to inputted image data, a plurality of pixels including the target pixel being arranged in a matrix manner, includes an NR circuit (106). The NR circuit (106) includes a signal processing process circuit (114) for carrying out subtraction or addition, with respect to a pixel value Aij of the target pixel, of a value equivalent to a noise quantity Er calculated in advance, in a case where the pixel value Aij of the target pixel is larger or smaller, respectively, than a first couple of estimated values Bij and Cij for the pixel value Aij of the target pixel, the first couple of estimated values Bij and Cij being estimated from pixel values of respective pixels adjacent to the target pixel, centered at the target pixel, in a temporal axis or in a spatial axis.

Abstract: A signal processing device (201) includes noise reduction units (101), cascade-connected to each other, each of which includes: a signal selection section (31) for selecting a representative value from sampled signals obtained from an input signal by sampling a target signal and signals which are away from the target signal by given intervals; a voltage determination section (51) for determining which of a determined representative value and a voltage of the target signal is larger; and a signal output section (61) for increasing or decreasing the voltage of the target signal depending on a result of the determining and outputs the target signal as the output signal. A combination of intervals between the target signal and the signals excluding the target signal vary from noise reduction unit (101) to noise reduction unit (101). A noise reduction unit on a more upstream side has a larger maximum value of the intervals.

Abstract: An apparatus and a method for adaptive filtering includes an antenna that receives analog video broadcast signal data; an analog-to-digital converter coupled to the antenna and converting the received analog video broadcast signal data to digital video signal data; a frame buffer memory storing the digital video signal data; an instruction memory storing adaptive filtering instructions; and an adaptive filter coupled to the memory and the analog-to-digital converter, wherein the adaptive filter: reads the adaptive filter instructions from the memory; executes the adaptive filter instructions; averages an input pixel with a corresponding pixel stored in the frame buffer memory; calculates a forgetting factor for each pixel in the plurality of pixel values stored in the frame buffer memory; and filters noise from each pixel of the plurality of pixel values stored in the frame buffer memory based on the forgetting factor.

Abstract: A method for de-interlacing interlaced video includes receiving a first video field and a second video field, generating a first video frame by inserting the first video field in the first video frame on every second line of the first video frame, and by inserting a first synthesized video field on the lines of the first video frame not populated by the first video field. The video data of the first synthesized video field is based on video data of the first and second video fields. A second video frame is generated by inserting the second video field in the first video frame on every second line of the second video frame and by inserting a second synthesized video field on the lines of the second video frame not populated by the second video field. Two de-interlaced video frames are output for every received interlaced video frame.

Abstract: Several systems and methods for filtering noise from a picture in a picture sequence associated with video data are disclosed. In an embodiment, the method includes accessing a plurality of pixel blocks associated with the picture and filtering noise from at least one pixel block from among the plurality of pixel blocks. The filtering of noise from a pixel block from among the at least one pixel block includes identifying pixel blocks corresponding to the pixel block in one or more reference pictures associated with the picture sequence. Each identified pixel block is associated with a cost value. One or more pixel blocks are selected from among the identified pixel blocks based on associated cost values. Weights are assigned to the selected one or more pixel blocks and set of filtered pixels for the pixel block is generated based on the weights.

Abstract: A filter for a video stream is provided. The filter generates a filtered picture according to a current picture and its previous picture. A motion difference calculator accumulates differences between current picture values and previous picture values within a neighborhood of each pixel to provide a corresponding motion difference. A histogram counter performs histogram counting according to motion differences of the pixels. A filter value calculator provides a filter value for each pixel according to operations of the motion difference calculator and the histogram counter. A blender blends the current picture value and the previous picture value of each pixel according to weightings correlated to the filter value, and provides a filtered picture value for each pixel of the filtered picture.

Abstract: In one system embodiment, an overlapped block processing module configured to provide three-dimensional (3D) denoising of plural frames corresponding to a raw video sequence; and a frame alignment module configured to represent the raw video sequence with motion compensated frames corresponding to the raw video sequence, the motion compensated frames consisting of the plural frames and fewer in quantity than the quantity of frames of the raw video sequence, the plural frames based on prior temporally matched frames corresponding to the raw video sequence.

Abstract: Disclosed herein is a movement-adaptive noise reduction apparatus, including a memory, a mixing control section, a movement component extraction section, a low-pass filter section, and a movement decision control section. In the apparatus, the movement decision control section and the low-pass filter section receive, from the outside, information regarding the gain value upon an amplification process to which the image signal is subjected before inputted to the mixing control section to control at least one of the threshold value and the filter characteristic in response to the information.

Abstract: A video processing system may receive a current raw video frame and may estimate motion between the current frame and a previous frame to determine motion vectors (mv). Based on the same mvs, motion compensated (MC) noise reduction may be performed and MC frame rate conversion (FRC) may generate a new frame. The previous frame may be noise reduced and/or a raw video frame. A MC frame may be generated based on the previous video frame and the mvs. Noise reduction may comprise blending the current raw frame with the MC frame. A blending factor may be determined based on similarity between pixels of the current video frame and MC pixels of the previous frame. The mvs may be scaled for FRC. Noise reduction may be performed in parallel and/or prior to the FRC depending on whether raw or noise reduced frames are utilized.

Abstract: An image processing circuit and a method thereof are provided herein. The image processing circuit has a first scaling circuit, a plurality of line buffers, a first sharpness circuit, a second scaling circuit, and a second sharpness circuit. The first scaling circuit enlarges an input image along a first direction to generate a first enlarged image. The line buffers temporarily store the pixel values of a plurality of pixel rows of the first enlarged image. The first sharpness circuit vertically sharpens the first enlarged image to generate a first sharpened image. The second scaling circuit enlarges the first sharpened image along a second direction to generate a second enlarged image. The second sharpness circuit horizontally sharpens the second enlarged image to generate a second sharpened image. Accordingly, it is possible to use the line buffers having shorter data lengths to perform the vertical sharpening.

Abstract: Apparatus and methods of motion detection for mosquito noise reduction in video sequences are provided. In one aspect, a method of motion detection in a sequence of digital images classifies a pixel of a plurality of pixels of a current image frame represented by a digital video input signal as a motion or non-motion pixel. A motion value for the pixel is calculated based on the classification of the pixel. The motion value is mapped to a coefficient of a temporal filter based on a control curve. A digital video output signal is generated based on the coefficient.

Abstract: Luminous elements of the three colors red, green and blue of video display devices have a different response time. Therefore, a colored edge and trail appear at edges in direction of a moving object. In order to reduce the disturbing character of such colored edges and trails, a horizontal spatial equalization of the response time of luminous elements having a shorter response time by low-pass filtering a component signal of the video component signals for driving luminous elements having a shorter response time dependent on a horizontal speed of changes of the component signal is recommended to reduce phosphor lag artifacts on display devices. The arrangement for processing video component signals of different color comprises a compensation unit which according to a preferred embodiment is realized by a FIR filter and a horizontal speed correction unit supplied with a horizontal and vertical motion estimation signal.

Abstract: Provided are a method and apparatus for removing image noise. The method includes: separating an input image signal into a signal component and a noise component; converting the noise component into a decorrelated noise component that is spatiotemporally decorrelated from neighboring pixels; and generating an image signal by adding the decorrelated noise component to the signal component.

Abstract: An LCD device and an LCD driving method select one among a plurality of threshold values provided along gray level regions of the pixel data as a threshold value for pixel data in a current frame interval. Accordingly, the number of times over-driving occurs due to noise when a still image is displayed can be minimized.

Abstract: Calculating a temporal filter values to filter video data for noise and ghosting artifacts. A sensor specific noise model may be derived using the video capture settings of the video source to estimate the noise variance for an image, and to determine the amount of the temporal filtering to be applied to a frame or pixel. The global motion and sensor specific noise model may be used to populate filter coefficient look-up tables based on the local motion and luma values of each pixel in the frame. The maximum absolute difference between frames may be used to estimate global motion between two frames such that filter strength may be reduced for frames exhibiting high global motion and increased for frames exhibiting low global motion. According to an embodiment, the increase in temporal filtering between frames may be capped to avoid sudden visible noise differences between frames.

Abstract: An electrical apparatus to reduce noise and minimize a drop in resolution. A recording unit records a processing target frame image and prior and future frame images; a first pixel-extracting section extracts pixels in a prescribed region; a second pixel-extracting section extracts pixels in a region corresponding to the prescribed region in the prior and future frame images; a first distance calculating section calculates temporospatial distances; a second distance calculating section calculates inter-pixel-value distances; and a noise reduction section reduces the processing target frame image on the basis of the temporospatial distance and the inter-pixel-value distance.

Abstract: When a printer starts a printing operation using a rolled sheet having IC chips, it is determined whether an error occurred while an IC chip writing device writes information to the IC chips. First page information specifying a page region in which an error occurred and second page information specifying a page region which has been subjected to the printing operation using the printer at a time of occurrence of the error are transmitted to a host computer. Then, recovery information generated using the host computer is obtained, and a print restarting position of a recording medium is controlled so that an information writing position at the time of occurrence of the error corresponds to a position in which the printing operation is restarted. Thereafter, the printing operation is restarted from the printing restarting position in accordance with the recovery information.

Abstract: Motion blur at a pixel of interest in a video signal is corrected adaptively by detecting a motion vector of the pixel of interest, estimating the direction and magnitude of the motion blur from the motion vector, and filtering the video signal at the pixel of interest. The filtering process uses the pixel values of the pixels in a neighborhood of the pixel of interest, clipped so that they do not differ too greatly from the pixel value of the pixel of interest, and low-pass filtering coefficients selected according to the estimated direction and magnitude. The filtered value is used to calculate a gain factor for correcting the pixel value of the pixel of interest. The strength of the correction is adjusted according to the difference between the pixel value of the pixel of interest and the mean pixel value in its vicinity. The adjustment and clipping prevent overcorrection.

Abstract: An image processing apparatus, in which an interpolation frame is inserted between a current frame and a first delayed frame preceding the current frame by one frame, includes a motion vector detector, a motion vector converter, and an interpolation frame generator; wherein the motion vector detector includes a test interpolator outputting test interpolation data, an interpolation data evaluator evaluating a correlation of each of the test interpolation data with reference to the first-delayed-frame block data, thereby outputting evaluation data indicating results of the evaluating, and a motion vector determiner outputting a motion vector of an item of the evaluation data having highest correlation in the plurality of items of the evaluation data; and the first to third test interpolation data are obtained as the test interpolation data from a plurality of items of the second-delayed-frame block data and a plurality of items of the current-frame block data.

Abstract: A method and unit for noise reduction in a current image frame, wherein the current image frame is a part of a sequence of image frames. The method compares a current pixel value of a pixel within the current image frame with a corresponding pixel value of the pixel in at least one adjacent image frame, and determines a piled-up value of the current pixel value and the corresponding pixel value if a pixel difference between the current pixel value and the corresponding pixel value is below a pixel threshold, wherein the pixel threshold depends on the corresponding pixel value and/or the current pixel value. The method and unit can be applied for block and color processing as well.

Abstract: A image-driving method for a display includes receiving an image frame and registering at least a part of the image frame, wherein the image frame is divided into a prior-part frame and a post-part frame; respectively conducting a first luminance adjustment on the prior-part frame and the post-part frame so as to take the adjustment results as a first part of a first image frame and a first part of a second image frame; filling the previous received image frame after a second luminance processing into a second part of the first image frame; filling the presently received image frame after a second luminance processing into a second part of the second image frame; outputting the complete first image frame and the complete second image frame for successive displaying.

Abstract: In one embodiment of the invention, decompressed video signals are upscaled and then filtered using a combined mosquito noise reduction (MNR) and aliasing coring filter that reduces both mosquito noise in the decompressed video signals as well as aliasing noise resulting from the upscaling process. In one implementation, the combined coring filter includes a dual-band filter having two passbands interleaved with two stopbands. The strength of the coring filter may be dynamically controlled based on compression information (e.g., quantizer scales indicative of video quality) associated with the compressed video bitstream from which the decompressed video is recovered.

Abstract: In one embodiment, a method is provided for performing motion compensated interpolation wherein, for any pixels in the interpolated frame to which there is neither a forward vector nor a backward vector projecting: including the pixel in an intermediate frame conceal area if it is not located within the full frame reveal area; including the pixel in an intermediate frame reveal area if it is not located within the full frame conceal area; and using the intermediate frame conceal and reveal areas to interpolate values for pixels within an area of the interpolated frame.

Abstract: A system and method for video frame interpolation are disclosed. In one embodiment, the method comprises receiving first motion estimation data representing estimated motion of blocks between a first frame and a second frame, receiving second motion estimation data representing estimated motion of blocks between the second frame and a third frame, determining whether an area in an interpolated frame between the first and second frame is an occlusion area based at least in part on the first and second motion estimation data, and estimating characteristics of pixels of the area based in part on the determination.

Abstract: A system and method for estimating random noise in an image frame or a sequence of image frames are presented. In some embodiments, the method includes performing Global Noise Estimation by comparing current and past filtered frames; converting global noise estimates into local noise estimates using estimated noise parameters based on current input image's local mean intensity; and providing local noise estimates to an adapted generic spatio-temporal filter. A parameter-based noise model is applied in the noise calculation.

Abstract: A method for video processing based on motion-aligned spatio-temporal steering kernel regression may include estimating local spatio-temporal steering parameters at pixels in input video data. The method may also include using the local spatio-temporal steering parameters to apply motion-aligned spatio-temporal steering kernel regression to the input video data to perform at least one of upscaling and noise smoothing.

Abstract: Aspects of the present invention relate to creation, modification and implementation of dither pattern structures applied to an image to diminish contouring artifacts. Some aspects relate to dither pattern structures with pixel values in a first color channel pattern that are spatially dispersed from pixel values in a corresponding pattern in a second color channel. Some aspects relate to application. Some aspects relate to systems and apparatus for creation and application of these dither pattern structures comprising pixel values dispersed across color channels.

Abstract: A method for adaptive spatio-temporal filtering is disclosed. Local motion vectors between a current video frame and other nearby video frames are determined. Local motion-aligned temporal confidence parameters are determined. Local spatial orientation parameters are determined. The local motion vectors, the local motion-aligned temporal confidence parameters, and the local spatial orientation parameters are used to adaptively determine spatio-temporal kernel weights. The spatio-temporal kernel weights are used to perform spatio-temporal filtering on input video data.

Abstract: A video processing method and apparatus for a liquid crystal display (LCD) device is disclosed. The video processing method for the LCD device includes detecting noise by comparing data of a previous frame with data of a current frame, if the noise is detected, removing the noise from the current frame data, and outputting the resultant current frame data having no noise together with the previous frame data, and comparing the previous frame data with the resultant current frame data having no noise in a lookup table, selecting overdriving data corresponding to the comparison result, and outputting the selected overdriving data.

Abstract: A video noise reducer processes a frame difference signal equal to the difference between the video signal of the current frame and the video signal of the preceding frame or the difference between the video signal of the current frame and the noise-reduced video signal of the preceding frame to obtain a motion detection signal and a noise detection signal. The difference between the motion detection signal and the noise detection signal is then processed to obtain a recursion coefficient. The frame difference signal is multiplied by the recursion coefficient and the resulting product is additively combined with the video signal of the current frame to reduce noise without generating significant motion artifacts.

Abstract: Noise-reduced pixels may be generated using outputs of filtering via a first filter and/or a second filter, and/or a blend of both outputs. Blending a current pixel and an output of filtering of current pixel via the first filter may generate a first blended current pixel. Filtering via the first filter may be based on the current pixel, a previous collocated pixel, and a next collocated pixel. Blending the current pixel and an output of filtering of current pixel via the second filter may generate a second blended current pixel. Filtering via the second filter may be based on the current pixel and a collocated pixel of the previous second blended video image or of the previous filtered output video image. Blending the first blended current pixel and the second blended current pixel using an adaptive blending factor may dynamically generate a filtered output pixel.

Abstract: The present invention provides a noise reduction apparatus and method thereof. The noise reduction apparatus includes a first detecting logic, a second detecting logic, a first noise filtering logic, a second noise filtering logic, and an output logic. The first detecting logic detects if a video signal has a first noise characteristic. The second detecting logic detects if the video signal has a second noise characteristic. The first noise filtering logic performs a first noise filtering process upon the video signal to generate a first filtered signal. The second noise filtering logic performs a second noise filtering process upon the video signal to generate a second filtered signal. The output logic receives the first filtered signal and the second filtered signal, and references detection results provided by the first detecting logic and the second detecting logic when generating an output signal.

Abstract: The present invention relates to a video picture display method that aims to reduce the effects of blurring and multiple contours when the picture display frequency is doubled. According to the invention, for each source video picture, a video level dissymmetry is created between the two pictures from the source video picture after doubling the frequency in the areas in motion of the source video picture.

Abstract: The invention provides an image processing apparatus for processing an interlaced video which includes a judging module, a determining module and a processing module. The judging module is used for judging if a pixel in the kth frame among P frames of the interlaced video relates to a moving object. If the result judged by the determining module is YES, the determining module determines one between two pixels adjacent to the judged pixel in the frame as an edge pixel relative to an edge of the moving object. The first processing module is used for calculating a gray scale of the edge pixel determined by the determining module in an average way.

Abstract: An apparatus outputs an image signal for each frame, divides a frame into sub-frames, acquires a first signal of high frequency components and a second signal of low frequency components of a sub-frame, and generates a third signal by multiplying the second signal by K. If a fourth signal obtained by adding the third signal to the first signal falls within a predetermined range, the apparatus outputs the third signal, whereas if the fourth signal includes a portion exceeding the range, the apparatus outputs a signal obtained by correcting the third signal. The apparatus also generates a composition signal of the output signal and the first signal and a fifth signal by multiplying the third signal by a correction amount y of the third signal. As a sub-frame of interest, either the composition signal or the fifth signal is output.

Abstract: According to one embodiment, an input image signal is passed through a plurality of first high pass filters having different passing frequency band to generate level histograms. High frequency component noise reduction processing is applied to the output of one of the first high pass filters selected based on one of the generated histograms that satisfies a predetermined threshold, low frequency component noise reduction processing is applied to a result obtained by subtracting the output of the selected first high pass filter from the input image signal, and outputs obtained by both the noise reduction processing are added.

Abstract: A dynamic motion degree of a video composite signal is estimated. A chrominance signal after Y/C separation and chrominance demodulation is narrow-band low pass filtered (NBLPF) and wide-band low pass filtered (WBLPF), so as to generate a narrow-band filtered signal and a wide-band filtered signal. The narrow-band filtered signal and the wide-band filtered signal are weighted based on the estimated dynamic motion degree, so as to determine how much high frequency component of the chrominance signal is reserved. In the static image processing, more high frequency component is reserved, so as to reduce the color transition issue and keep the image color being sharp. In the dynamic image processing, more high frequency component is filtered, so as to reduce the cross color issue.

Abstract: An apparatus for processing an image includes a motion vector detector, a motion-blurring-mitigated image generator, and a spatial resolution creation unit. The motion vector detector is configured to detect a motion vector by using an image that is made up of multiple pixels and acquired by an image sensor having time integration effects. The motion-blurring-mitigated image generator is configured to generate a motion-blurring-mitigated image in which motion blurring of a moving object is mitigated by using the motion vector detected by the motion vector detector on the assumption that a pixel value of pixel of the moving object in the image is a value obtained by integrating, in a time direction, a pixel value of each pixel in which no motion blurring that corresponds to the moving object occur as it is moved.

Abstract: An apparatus for suppressing noise of a video signal. The apparatus includes: a difference-signal generation section generating a difference signal being a field or frame difference between the input and the output video signals; a noise compensation-signal generation section generating a noise compensation signal; a noise-compensation signal subtraction section; and a feedback-ratio control section, wherein the feedback-ratio control section includes a signal-level determination section determining a signal level of the difference signal for each area and detecting an abrupt change in an input signal, a count section counting the number of input fields or frames from the time of an abrupt change in a signal level to the subsequent abrupt change, and a feedback-ratio setting section setting a feedback ratio for the area in accordance with a count value, wherein the feedback-ratio setting section sets the feedback ratio such that the ratio gradually increases as the count value increases.

Abstract: An image processing system implements recursive 3D super precision for processing smoothly changing video image areas by performing temporal noise reduction and then 2D super precision. The temporal noise reduction is applied to two frames, one being the current input low precision frame, and the other being the previous higher precision frame from memory. The 2D super precision is applied to the noise reduced frame to output a high precision frame which is also saved into memory for processing the next incoming frame. The input frame has a limited bit depth while the output image has an increased bit depth.

Abstract: A hybrid intra-inter bi-predictive (or multi-predictive) coding mode allows both intraframe (intra) and interframe (inter) predictions to be combined together for hybrid-encoding a current macroblock or a subblock. Bi-prediction may be used also in I-pictures, combining two intra predictions that use two different intra prediction directions. A video encoder processes data representing a two-dimensional video image which has been produced by a conventional commercially available video camera. The video encoder is adapted to select, for coding a current macroblock, between an intra encoding mode, an P-frame inter encoding mode, a B-frame bi-predictive inter mode, and a hybrid intra-inter bi-predictive encoding mode. A video decoder receives and decodes a data stream that may contain a block/macroblock encoded in accordance with the hybrid intra-inter bi-predictive encoding mode.

Abstract: A hybrid intra-inter bi-predictive (or multi-predictive) coding mode allows both intraframe (intra) and interframe (inter) predictions to be combined together for hybrid-encoding a current macroblock or a subblock. Bi-prediction may be used also in I-pictures, combining two intra predictions that use two different intra prediction directions. A video encoder processes data representing a two-dimensional video image which has been produced by a conventional commercially available video camera. The video encoder is adapted to select, for coding a current macroblock, between an intra encoding mode, an P-frame inter encoding mode, a B-frame bi-predictive inter mode, and a hybrid intra-inter bi-predictive encoding mode. A video decoder receives and decodes a data stream that may contain a block/macroblock encoded in accordance with the hybrid intra-inter bi-predictive encoding mode.

Abstract: A method for reducing cross-luminance in an image display device includes receiving luminance signals of a plurality of frames in a composite video signal, determining a movement condition of a first frame of the plurality of frames according to the luminance signals, performing a filtering operation for the first frame according to the movement condition of the first frame, and outputting a result of the filtering operation.

Abstract: A method and system for analog video noise detection are provided. A motion metric (MM) value may be determined for pixels in a video image. The MM values may be collected and accumulated for a number of noise level intervals to determine average noise levels for each interval. An early-exit algorithm (EEA) or an interpolation estimate algorithm (IEA) may be utilized to determine the noise level. The EEA may select the noise level based on a first noise level interval with a number of collected samples larger than a threshold. The IEA may determine the noise level based on an average of a plurality of noise levels associated with consecutive noise level intervals with collected samples that are larger than the threshold. A noise level indicator (NLI) may be the noise level of the current image or an average based on noise levels from the current and previous images.

Abstract: According to one embodiment, a method is disclosed. The method includes receiving video data, measuring a temporal feature of motion movement of the data, measuring per-pixel spatial content features of the data, performing a local content analysis to classify pixels; and performing noise reduction filtering on the pixels.

Abstract: A method and system for content adaptive analog video noise detection are provided. A motion metric (MM) value, an edge detection value, and a content detection value may be determined for pixels in a video image. The MM values of pixels with edge detection values smaller than an edge threshold value and with content detection values smaller than a content threshold value may be collected and accumulated for a portion of the noise level intervals when the MM values fall in this interval. The MM values collected and accumulated may be utilized to determine an average noise level for each of the intervals. A noise level indicator (NLI) for the current video image may be determined based on the noise level of the current image or on the noise levels of the current and at least one previous video images.

Abstract: A video noise reducer reduces the noise artifacts in a video signal. The video noise reducer is reconfigurable to provide spatial noise reduction and temporal noise reduction in either a parallel or cascade architecture. The video noise reducer is self-calibrating by providing estimation modules that estimate the amount of noise in the video signal and a noise injector that confirms the measurement against a known quantity of noise. The video noise reducer is adaptive to solutions in hardware or a combination of hardware and firmware. The video noise reducer is also optimized for efficient memory usage in interlaced video signal processing applications.