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📄 remapim.m

📁 MATLAB Functions for Multiple View Geometry
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% REMAPIM - Remaps image intensity values%% Usage:   newim = remapim(im, x, y, rescale)%                                        \%                                      optional% Arguments%            im  - Image to be transformed.%            x,y - Coordinates of spline control points that define the%                  mapping function.  These coordinates are in  the range%                  0-1 and are typically obtained experimentally via the%                  function GREYTRANS%            rescale - An optional flag (0 or 1) indicating whether image%                      values should  be normalised to the range 0-1. %                      This is only provided for speed when called%                      by GREYTRANS.  By default the input image will%                      be normalised to the range 0-1.%% Image intensity values are remapped to new values via a mapping% function defined by a series of spline points.  The mapping function is% defined over the range 0-1, accordingly the input image is normalised% to the range 0-1.  The output image will also lie in this range.  % Copyright (c) 2002-2003 Peter Kovesi% School of Computer Science & Software Engineering% The University of Western Australia% http://www.csse.uwa.edu.au/% % Permission is hereby granted, free of charge, to any person obtaining a copy% of this software and associated documentation files (the "Software"), to deal% in the Software without restriction, subject to the following conditions:% % The above copyright notice and this permission notice shall be included in % all copies or substantial portions of the Software.%% The Software is provided "as is", without warranty of any kind.% April 2002 - original version.% March 2003 - modified to work with colour images.function nim = remapim(im, x, y, rescale)    if nargin < 4	rescale = 1;    end        if ndims(im)==3        % Assume we have a colour image        hsv = rgb2hsv(im);        % Apply remapping just to the value component        hsv(:,:,3) =  remap(hsv(:,:,3), x, y, rescale);        nim = hsv2rgb(hsv);    else                   % Assume we have a 2D greyscale image	nim = remap(im, x, y, rescale);    end% Internal function that does the workfunction nim = remap(im, x, y, rescale)        if rescale	im = normalise(im);    end        nim = spline(x,y,im);  % Remap image values     % clamp image values within bounds 0 - 1    gt0 = nim > 0;    nim = nim.*gt0;   % values < 0 become 0        lt1 = nim < 1;    nim = nim.*lt1 + ~lt1;  % values > 1 become 1

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