www.gusucode.com > visionhdl工具箱matlab源码程序 > visionhdl/visionhdl/+visionhdl/en/DemosaicInterpolator.m
classdef DemosaicInterpolator< matlab.system.mixin.CustomIcon & matlab.system.mixin.Propagates & visionhdl.internal.abstractLineMemoryKernel & matlab.system.mixin.Nondirect
%DemosaicInterpolator Performs Demosaicing of an input image in Bayer
% format with the specified alignment. The alignment is identified as
% the sequence of R, G and B pixels for the top left 2x2 neighborhood of the input image.
%
% demosaicInterpolate = visionhdl.DemosaicInterpolator returns a System object, demosaicInterpolate,
% that performs demosaicing of a Bayer pattern encoded input stream,
% based on the input control signals.
%
% demosaicInterpolate = visionhdl.DemosaicInterpolator('PropertyName',PropertyValue,...)
% returns a HDL Demosaic System object demosaicInterpolate, with each specified
% property set to the specified value.
%
% When Bilinear Interpolation is selected, the interpolated pixel is found
% simply by averaging a neighborhood of 3x3 pixels. When Gradient-Corrected
% Bilinear Interpolation is selected, the interpolated pixel is found
% through a process of averaging, and applying a correction based on the
% local gradient of a 5x5 neighborhood. This has a higher complexity,
% however achieves a higher PSNR than Bilinear Interpolation.
%
% Step method syntax:
% [pixOut,ctrlOut] = step(demosaicInterpolate,pixIn,ctrlIn)
% returns the interpolated R,G,B values based on the input data
% and input control signals.
%
% The input pixIn is a scalar image pixel and the data type can be
% double/single, unsigned integer, or fixed point. The
% data type of output pixOut follows that of pixIn. Signed data
% types are not supported for simulation or HDL code generation.
% ctrlIn and ctrlOut are structures consisting of five
% control signals. See also <a href="matlab:doc visionhdl.FrameToPixels">visionhdl.FrameToPixels</a> or <a href="matlab:doc pixelcontrolstruct">pixelcontrolstruct</a>.
%
% 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.
%
% DemosaicInterpolator methods:
%
% step - See above description for use of this method
% release - Allow property value and input characteristics changes
% clone - Create demosaicInterpolate object with same property values
% isLocked - Locked status (logical)
%
% DemosaicInterpolator properties: -
%
% Algorithm - Choose algorithm used to perform interpolation.
% SensorAlignment - Alignment of the input image.
% LineBufferSize - Size of line buffer memory, equivalent to largest row.
%
% % EXAMPLE:
% % Form an [R G B] output image from a Bayer format input.
% % Set the dimensions of the test image
% frmActivePixels = 256;
% frmActiveLines = 192;
%
% % Load the source image
% % This image is in Bayer pattern: each pixel is represented by one value,
% % alternating green values with red and blue values.
% frmOrig = imread('mandi.tif');
% figure
% imshow(frmOrig,'InitialMagnification',20)
% title 'Full Image (Scaled Down)'
%
% % Select a portion of the image matching the desired test size.
% % These offsets select the face of the woman in the image.
% frmInput = frmOrig(900:899+frmActiveLines,2350:2349+frmActivePixels);
% figure
% imshow(frmInput)
% title 'Input Image'
%
% % Create serializer and specify size of inactive pixel regions
% frm2pix = visionhdl.FrameToPixels(...
% 'NumComponents',1,...
% 'VideoFormat','custom',...
% 'ActivePixelsPerLine',frmActivePixels,...
% 'ActiveVideoLines',frmActiveLines,...
% 'TotalPixelsPerLine',frmActivePixels+10,...
% 'TotalVideoLines',frmActiveLines+10,...
% 'StartingActiveLine',6,...
% 'FrontPorch',5);
%
% % Create demosaic interpolator
% % Specify the sequence of color values matching the 2-by-2 pixels in the top-left corner of the image.
% demosaicInterpolate = visionhdl.DemosaicInterpolator(...
% 'SensorAlignment', 'RGGB');
%
% % Serialize the test image
% % pixIn is a vector of pixel values
% % ctrlIn is a vector of control signal structures
% [pixIn,ctrlIn] = step(frm2pix,frmInput);
%
% % Prepare to process pixels
% [~,~,numPixelsPerFrame] = getparamfromfrm2pix(frm2pix);
% ctrlOut = repmat(pixelcontrolstruct,numPixelsPerFrame,1);
% pixOut = zeros(numPixelsPerFrame,3,'uint8');
%
% % For each pixel in the stream, generate the {R,G,B} triplet
% % Print a progress message every 32 lines
% lineCount = 1;
% for p = 1:numPixelsPerFrame
% if ctrlIn(p).hEnd
% lineCount = lineCount + 1;
% if mod(lineCount,32) == 0
% fprintf('Processing... line %d\n',lineCount);
% end
% end
% [pixOut(p,:),ctrlOut(p)] = step(demosaicInterpolate,pixIn(p),ctrlIn(p));
% end
%
% % Create deserializer with format matching that of the serializer
% pix2frm = visionhdl.PixelsToFrame(...
% 'NumComponents',3,...
% 'VideoFormat','custom',...
% 'ActivePixelsPerLine',frmActivePixels,...
% 'ActiveVideoLines',frmActiveLines);
%
% % Convert the pixel stream to an image frame
% [frmOutput,frmValid] = step(pix2frm,pixOut,ctrlOut);
% if frmValid
% figure
% imshow(frmOutput)
% title 'Output Image'
% end
% See also demosaic.
% Copyright 2014-2016 The MathWorks, Inc.
methods
function out=DemosaicInterpolator
%DemosaicInterpolator Performs Demosaicing of an input image in Bayer
% format with the specified alignment. The alignment is identified as
% the sequence of R, G and B pixels for the top left 2x2 neighborhood of the input image.
%
% demosaicInterpolate = visionhdl.DemosaicInterpolator returns a System object, demosaicInterpolate,
% that performs demosaicing of a Bayer pattern encoded input stream,
% based on the input control signals.
%
% demosaicInterpolate = visionhdl.DemosaicInterpolator('PropertyName',PropertyValue,...)
% returns a HDL Demosaic System object demosaicInterpolate, with each specified
% property set to the specified value.
%
% When Bilinear Interpolation is selected, the interpolated pixel is found
% simply by averaging a neighborhood of 3x3 pixels. When Gradient-Corrected
% Bilinear Interpolation is selected, the interpolated pixel is found
% through a process of averaging, and applying a correction based on the
% local gradient of a 5x5 neighborhood. This has a higher complexity,
% however achieves a higher PSNR than Bilinear Interpolation.
%
% Step method syntax:
% [pixOut,ctrlOut] = step(demosaicInterpolate,pixIn,ctrlIn)
% returns the interpolated R,G,B values based on the input data
% and input control signals.
%
% The input pixIn is a scalar image pixel and the data type can be
% double/single, unsigned integer, or fixed point. The
% data type of output pixOut follows that of pixIn. Signed data
% types are not supported for simulation or HDL code generation.
% ctrlIn and ctrlOut are structures consisting of five
% control signals. See also <a href="matlab:doc visionhdl.FrameToPixels">visionhdl.FrameToPixels</a> or <a href="matlab:doc pixelcontrolstruct">pixelcontrolstruct</a>.
%
% 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.
%
% DemosaicInterpolator methods:
%
% step - See above description for use of this method
% release - Allow property value and input characteristics changes
% clone - Create demosaicInterpolate object with same property values
% isLocked - Locked status (logical)
%
% DemosaicInterpolator properties: -
%
% Algorithm - Choose algorithm used to perform interpolation.
% SensorAlignment - Alignment of the input image.
% LineBufferSize - Size of line buffer memory, equivalent to largest row.
%
% % EXAMPLE:
% % Form an [R G B] output image from a Bayer format input.
% % Set the dimensions of the test image
% frmActivePixels = 256;
% frmActiveLines = 192;
%
% % Load the source image
% % This image is in Bayer pattern: each pixel is represented by one value,
% % alternating green values with red and blue values.
% frmOrig = imread('mandi.tif');
% figure
% imshow(frmOrig,'InitialMagnification',20)
% title 'Full Image (Scaled Down)'
%
% % Select a portion of the image matching the desired test size.
% % These offsets select the face of the woman in the image.
% frmInput = frmOrig(900:899+frmActiveLines,2350:2349+frmActivePixels);
% figure
% imshow(frmInput)
% title 'Input Image'
%
% % Create serializer and specify size of inactive pixel regions
% frm2pix = visionhdl.FrameToPixels(...
% 'NumComponents',1,...
% 'VideoFormat','custom',...
% 'ActivePixelsPerLine',frmActivePixels,...
% 'ActiveVideoLines',frmActiveLines,...
% 'TotalPixelsPerLine',frmActivePixels+10,...
% 'TotalVideoLines',frmActiveLines+10,...
% 'StartingActiveLine',6,...
% 'FrontPorch',5);
%
% % Create demosaic interpolator
% % Specify the sequence of color values matching the 2-by-2 pixels in the top-left corner of the image.
% demosaicInterpolate = visionhdl.DemosaicInterpolator(...
% 'SensorAlignment', 'RGGB');
%
% % Serialize the test image
% % pixIn is a vector of pixel values
% % ctrlIn is a vector of control signal structures
% [pixIn,ctrlIn] = step(frm2pix,frmInput);
%
% % Prepare to process pixels
% [~,~,numPixelsPerFrame] = getparamfromfrm2pix(frm2pix);
% ctrlOut = repmat(pixelcontrolstruct,numPixelsPerFrame,1);
% pixOut = zeros(numPixelsPerFrame,3,'uint8');
%
% % For each pixel in the stream, generate the {R,G,B} triplet
% % Print a progress message every 32 lines
% lineCount = 1;
% for p = 1:numPixelsPerFrame
% if ctrlIn(p).hEnd
% lineCount = lineCount + 1;
% if mod(lineCount,32) == 0
% fprintf('Processing... line %d\n',lineCount);
% end
% end
% [pixOut(p,:),ctrlOut(p)] = step(demosaicInterpolate,pixIn(p),ctrlIn(p));
% end
%
% % Create deserializer with format matching that of the serializer
% pix2frm = visionhdl.PixelsToFrame(...
% 'NumComponents',3,...
% 'VideoFormat','custom',...
% 'ActivePixelsPerLine',frmActivePixels,...
% 'ActiveVideoLines',frmActiveLines);
%
% % Convert the pixel stream to an image frame
% [frmOutput,frmValid] = step(pix2frm,pixOut,ctrlOut);
% if frmValid
% figure
% imshow(frmOutput)
% title 'Output Image'
% end
% See also demosaic.
end
function getDiscreteStateImpl(in) %#ok<MANU>
% Return structure of states with field names as
% DiscreteState properties.
end
function getExecutionSemanticsImpl(in) %#ok<MANU>
% works in both classic and synchronous subsystems
end
function getHeaderImpl(in) %#ok<MANU>
%getHeaderImpl Return header for object display
end
function getIconImpl(in) %#ok<MANU>
end
function getInputNamesImpl(in) %#ok<MANU>
end
function getNumInputsImpl(in) %#ok<MANU>
end
function getNumOutputsImpl(in) %#ok<MANU>
end
function getOutputDataTypeImpl(in) %#ok<MANU>
end
function getOutputNamesImpl(in) %#ok<MANU>
end
function getOutputSizeImpl(in) %#ok<MANU>
end
function getPropertyGroupsImpl(in) %#ok<MANU>
%getPropertyGroupsImpl Return property groups for object display
end
function isOutputComplexImpl(in) %#ok<MANU>
end
function isOutputFixedSizeImpl(in) %#ok<MANU>
end
function loadObjectImpl(in) %#ok<MANU>
end
function outputImpl(in) %#ok<MANU>
% output
end
function resetImpl(in) %#ok<MANU>
% Initialize states
end
function saveObjectImpl(in) %#ok<MANU>
%Save the public properties
end
function setupImpl(in) %#ok<MANU>
end
function showSimulateUsingImpl(in) %#ok<MANU>
end
function updateImpl(in) %#ok<MANU>
% update states
end
function validateInputsImpl(in) %#ok<MANU>
%coder.extrinsic('validatecontrolsignals');
end
end
methods (Abstract)
end
properties
%Algorithm Interpolation algorithm
% Specify the interpolation algorithm as one of
% ['Gradient-corrected linear'|'Bilinear']
Algorithm;
%LineBufferSize Line buffer size
% Specify the maximum number of pixels in a horizontal line as an
% positive integer. The default value of this property is 2048.
LineBufferSize;
%SensorAlignment Sensor alignment
% Specify the sensor alignment as one of
% ['GBRG'|'GRBG']|'BGGR'|'RGGB']
SensorAlignment;
end
end