ADAPTIVE METHOD AND TELEVISION EQUALIZER THAT SUPPRESS VIDEO SIGNAL ECHO

    公开(公告)号:JPH07147646A

    公开(公告)日:1995-06-06

    申请号:JP12279994

    申请日:1994-06-03

    Abstract: PURPOSE: To suppress video signal echoes in a television equalizer. CONSTITUTION: A first digital filter 2 in television equalizer 1 supplies an output upon receiving a video signal x(k) and a first adding node 3 in the equalizer 1 supplies an equalizer output signal y(k) upon receiving the output of the filter 2. A digital filter 5 in the equalizer 1 supplies an output to the node 3 upon receiving the equalizer output signal y(k) and a second adding node in the equalizer 1 supplies an error signal e(k) which is equal to the difference between the equalizer output signal y(k) and a reference signal d(k). An echo suppressing circuit 4 supplies a filter coefficient updated upon receiving the error signal e(k) to the first and second digital filters 2 and 5.

    METHOD FOR REDUCING GAUSS NOISE IN FIELD ADAPTIVELY THROUGH THE USE OF FUZZY LOGIC PROCESSING

    公开(公告)号:JPH10336490A

    公开(公告)日:1998-12-18

    申请号:JP12835998

    申请日:1998-05-12

    Abstract: PROBLEM TO BE SOLVED: To suppress noise affected on a specific area of a field scanned by the unit of lines by replacing a pixel having noise with an average pixel value of a nearby pixel belonging to a prescribed processing window. SOLUTION: A difference calculation circuit calculates a difference Di (D1-D7) between luminance values Xi (X1-X7) of a pixel adjacent to a processing pixel value X of a processing window. Then a Dmax &Dmin detection block identifies a maximum value and a minimum value of a received difference Di. Upon the receipt of the Dmax and Dmin by an adaptive threshold level detection processing block adopting a 1st fuzzy logic, they are referenced as a membership 1 and corresponding values to the threshold levels Th1, Th2 are generated. Then a local adaptive noise smoothing processing block adopting a 2nd fuzzy block generates a set of output values Ki based on the threshold level parameters Th1, Th2 referenced by a membership 2 and generated before. A final filter block generates a pixel Xout as a sum of weighting factors.

    MOTION ESTIMATION AND COMPENSATION FIELD RATE UP CONVERSION METHOD FOR VIDEO, AND DEVICE FOR ACTUATING THE METHOD

    公开(公告)号:JPH11168703A

    公开(公告)日:1999-06-22

    申请号:JP11564598

    申请日:1998-04-24

    Abstract: PROBLEM TO BE SOLVED: To obtain a compensation field rate up method by evaluating an error function for each pair of image blocks, evaluating the extent of homogeneity property for each pair of estimation motion vectors, applying a fuzzy rule which has a start level for each pair of estimation motion vectors, deciding the best estimation motion vector of the pair and deciding an estimation motion vector of the image blocks. SOLUTION: A block C BUILD is supplied according to the output of a block FUZZY, an updating set is supplied to a component of a candidate motion vector C, and eight updating motion vectors are decided. An appropriate image block which is positioned by a motion vector that is selected by a block ADDGEN is decided, and the block ADDGEN is supplied by an output of a block VPROC and an output of the block C BUILD. Error function value that is related to eight updating motion vectors which are evaluated by a block SAD 2 is supplied to a block CSEL, and a motion vector related to image block is selected as an estimation motion vector.

    5.
    发明专利
    未知

    公开(公告)号:DE69727911D1

    公开(公告)日:2004-04-08

    申请号:DE69727911

    申请日:1997-04-24

    Abstract: A method and a device for motion estimated and compensated Field Rate Up-conversion (FRU) for video applications, providing for: a) dividing an image field to be interpolated into a plurality of image blocks (IB), each image block made up of a respective set of image elements of the image field to be interpolated; b) for each image block (K(x,y)) of at least a sub-plurality (Q1,Q2) of said plurality of image blocks, considering a group of neighboring image blocks (NBÄ1Ü-NBÄ4Ü); c) determining an estimated motion vector for said image block (K(x,y)), describing the movement of said image block (K(x,y)) from a previous image field to a following image field between which the image field to be interpolated is comprised, on the basis of predictor motion vectors (PÄ1Ü-PÄ4Ü) associated to said group of neighboring image blocks; d) determining each image element of said image block (K(x,y)) by interpolation of two corresponding image elements in said previous and following image fields related by said estimated motion vector. Step c) provides for: c1) applying to the image block (K(x,y)) each of said predictor motion vectors to determine a respective pair of corresponding image blocks in said previous and following image fields, respectively; c2) for each of said pairs of corresponding image blocks, evaluating an error function (errÄiÜ) which is the Sum of luminance Absolute Difference (SAD) between corresponding image elements in said pair of corresponding image blocks; c3) for each pair of said predictor motion vectors, evaluating a degree of homogeneity (H(i,j)); c4) for each pair of said predictor motion vectors, applying a fuzzy rule having an activation level (rÄkÜ) which is higher the higher the degree of homogeneity of the pair of predictor motion vectors and the smaller the error functions of the pair of predictor motion vectors; c5) determining an optimum fuzzy rule having the highest activation level (rÄoptÜ), and determining the best predictor motion vector (PÄminÜ) of the pair associated to said optimum fuzzy rule having the smaller error function; c6) determining the estimated motion vector for said image block (K(x,y)) on the basis of said best predictor motion vector (PÄminÜ).

    6.
    发明专利
    未知

    公开(公告)号:DE69724412D1

    公开(公告)日:2003-10-02

    申请号:DE69724412

    申请日:1997-05-12

    Abstract: The level of Gaussian noise in a memory field being scanned by rows is reduced by reconstructing each pixel by fuzzy logic processors, the latter processing the the values of pixels neighbouring the pixel being processed and belonging to a processing window defined by the last scanned row and the row being scanned, thus minimizing the memory requisite of the filtering system to a single row. The system perform an adaptive filtering within the current field itself and does not produce @ edge-smoothing @ effects as in prior adaptive filtering systems operating on consecutive fields.

    8.
    发明专利
    未知

    公开(公告)号:DE69736347D1

    公开(公告)日:2006-08-31

    申请号:DE69736347

    申请日:1997-05-09

    Abstract: Digital photography apparatus (100), particularly a digital still camera, comprising means (110-125) for acquiring a digital image, compression means (130) for obtaining a compressed image, and a memory (135) for storing the compressed image, the apparatus also including processing means (140) for obtaining a processed image and corresponding processing parameters from the image acquired, the processing means (140) supplying as an output, in a first operative condition, the processed image to be compressed by the compression means (130) and, in a second operative condition, the image acquired to be compressed by the compression means (130) and the processing parameters to be stored in the memory (135).

    10.
    发明专利
    未知

    公开(公告)号:DE69327900T2

    公开(公告)日:2000-07-06

    申请号:DE69327900

    申请日:1993-06-09

    Abstract: An adaptive method for suppressing video signal x(k) echoes in equalizers of TV sets including digital filters whose coefficients are updated in an adaptive and iterative manner using an LMS (Least Mean Square) algorithm until the difference, or output error, between a target output signal d(k), called the reference signal, and an outgoing signal y(k) from the equalizer is gradually reduced, comprises the steps of: applying a "combing" technique to an original filter having K*N coefficients in order to select K comb filters having N coefficients each; applying said LMS algorithm, with a variable convergence factor ( mu ) to each individual comb filter for a predetermined number of iterations; gathering the resultant configurations of the comb filter coefficients and selecting a subfilter with N largest modulo coefficients therefrom; updating the values of said N coefficients again by reiterating the LMS algorithm to said subfilter for a limited number of iterations; zeroing all the coefficients with a lower modulo than a predetermined threshold; selecting a group of F coefficients by a slotting operation across those of said coefficients which have a cluster value: and updating the value of said group of F coefficients, by reiterating the LMS algorithm, until the output error e(k) becomes smaller than a predetermined value.

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