gusucode.com > vision工具箱matlab源码程序 > vision/+vision/en/IDCT.m

    classdef IDCT< dsp.DCT
%IDCT 2-D inverse discrete cosine transform
%   HIDCT = vision.IDCT returns a System object, HIDCT, used to compute
%   the two-dimensional inverse discrete cosine transform (2-D IDCT) of a
%   real input signal. The number of rows and columns of the input matrix
%   must be a power of 2.
%
%   HIDCT = vision.IDCT('PropertyName', PropertyValue, ...) returns a 2-D
%   inverse discrete cosine transform System object, HIDCT, with each
%   specified property set to the specified value.
%
%   Step method syntax:
%
%   Y = step(HIDCT, X) computes the 2-D inverse discrete cosine
%   transform, Y, of input X.
%
%   System objects may be called directly like a function instead of using
%   the step method. For example, y = step(obj, x) and y = obj(x) are
%   equivalent.
%
%   IDCT methods:
%
%   step     - See above description for use of this method
%   release  - Allow property value and input characteristics changes
%   clone    - Create 2-D inverse discrete cosine transform object with
%              same property values
%   isLocked - Locked status (logical)
%
%   IDCT properties:
%
%   SineComputation - Method to compute sines and cosines
%
%   This System object supports fixed-point operations. For more
%   information, type vision.IDCT.helpFixedPoint.
%
%   % EXAMPLE: Use 2-D DCT to analyze the energy content in an image. Set
%   % the DCT coefficients lower than a threshold to 0 and reconstruct the
%   % image using 2-D IDCT.
%       hdct = vision.DCT;
%       I = double(imread('cameraman.tif'));
%       J = step(hdct, I);
%       imshow(log(abs(J)),[]), colormap(jet(64)), colorbar
%
%       hidct = vision.IDCT;
%       J(abs(J) < 10) = 0;
%       It = step(hidct, J);
%       figure, imshow(I, [0 255]), title('Original image')
%       figure, imshow(It,[0 255]), title('Reconstructed image')
%
%   See also vision.DCT.

 
%   Copyright 1995-2016 The MathWorks, Inc.

    methods
        function out=IDCT
            %IDCT 2-D inverse discrete cosine transform
            %   HIDCT = vision.IDCT returns a System object, HIDCT, used to compute
            %   the two-dimensional inverse discrete cosine transform (2-D IDCT) of a
            %   real input signal. The number of rows and columns of the input matrix
            %   must be a power of 2.
            %
            %   HIDCT = vision.IDCT('PropertyName', PropertyValue, ...) returns a 2-D
            %   inverse discrete cosine transform System object, HIDCT, with each
            %   specified property set to the specified value.
            %
            %   Step method syntax:
            %
            %   Y = step(HIDCT, X) computes the 2-D inverse discrete cosine
            %   transform, Y, of input X.
            %
            %   System objects may be called directly like a function instead of using
            %   the step method. For example, y = step(obj, x) and y = obj(x) are
            %   equivalent.
            %
            %   IDCT methods:
            %
            %   step     - See above description for use of this method
            %   release  - Allow property value and input characteristics changes
            %   clone    - Create 2-D inverse discrete cosine transform object with
            %              same property values
            %   isLocked - Locked status (logical)
            %
            %   IDCT properties:
            %
            %   SineComputation - Method to compute sines and cosines
            %
            %   This System object supports fixed-point operations. For more
            %   information, type vision.IDCT.helpFixedPoint.
            %
            %   % EXAMPLE: Use 2-D DCT to analyze the energy content in an image. Set
            %   % the DCT coefficients lower than a threshold to 0 and reconstruct the
            %   % image using 2-D IDCT.
            %       hdct = vision.DCT;
            %       I = double(imread('cameraman.tif'));
            %       J = step(hdct, I);
            %       imshow(log(abs(J)),[]), colormap(jet(64)), colorbar
            %
            %       hidct = vision.IDCT;
            %       J(abs(J) < 10) = 0;
            %       It = step(hidct, J);
            %       figure, imshow(I, [0 255]), title('Original image')
            %       figure, imshow(It,[0 255]), title('Reconstructed image')
            %
            %   See also vision.DCT.
        end

    end
    methods (Abstract)
    end
end