MatlabImageProcessing
Transcription
MatlabImageProcessing
Advanced MATLAB 046746 Topics • Data Types • Image Representation • Image/Video I/O • Matrix access • Image Manipulation • MEX - MATLAB Executable • Data Visualization • General Tips • Tricks Data Types • Relevant data types • • • • • double – default in most cases (usually 64 bit) single – when you want to save memory (usually 32 bit) uint8 – [0 255] – native for images uint16 – [0 65,535] Logical – [0 1] – native for masks • Simple casting: double(), uint8(). • Useful when displaying images with a dynamic range not corresponding to its actual type. • Conversion (of images): im2double(),im2uint8(),lab2double(),lab2uint8() • rgb2ind(),ind2rgb(),makecform() Common problem I = imread('world.jpg'); I2 = I-1.4; diffI = I-I2; fprintf('Max difference between images: %d\n',max(diffI(:))); Max difference between images: 1 fprintf('Max difference between images: %2.1f\n',max(diffI(:))); Max difference between images: 1.4 A much better practice is: display([ 'Max difference between images: ' num2str( max(diffI(:)) ) ]); Max difference between images: 1.4 Image Representation 2D Matrix • Intensity: Each pixel value in the dynamic range [minP, maxP]. • Can represent a grayscale image, results of a 2d function, etc. • Useful commands: imagesc(), axis, colormap(). • Binary: a.k.a masks. • Can represent absolute ground truth, etc. • Useful commands: bwlabel(),bwmorph(),bwdist(),im2bw(),bwperim(). Image Representation 2D Matrix • Indexed: Each pixel value in the range [minP, maxP]. • Can represent segmentation. • Useful commands: regionprops(),label2rgb() Image Representation 3D Matrix • True Color: Three 2D matrices stacked. Each represents a color component. (e.g. RGB) • Can represent an RGB color image, LAB image, etc. • Useful commands: imshow(),rgb2gray(),rgb2ind(). Image/Video I/O Useful Commands • • • • • • • • • imread() – read image imwrite() – write image im2frame() – convert image to movie frame movie2avi() – write avi file aviread() – read avi file mmreader()/VideoReader() – read video (better) VideoWriter() – create video file (2011b+) movie() – show movie implay() – show video interactively Matrix access Useful Commands: • Ind = sub2ind(matrixSize, rowSub, colSub) convert subscript to index. • [I,J] = ind2sub(siz,IND) – convert index to subscipt. • meshgrid() – generate X,Y grids. • F = scatteredInterpolant(x,y,v) - creates an interpolant that fits a surface of the form v = F(x,y). (replaced TriScatteredInterp) Image Manipulation Useful Commands: • • • • • • • • • • • imcrop()– Useful for interactive cropping. imrotate()– Rotate image. imfilter() – Use kernal to convolve/correlation. nlfilter() – Sliding neighborhood operation. blkproc() – Perform function on (semi-)distinct blocks. fspecial() – Create common image filter kernels. imresize() – Resize image using defined interpolation. kron() – Kronecker tensor product padarray() – Pad image. colfilt() – Colum-stack filtering (faster) imfreehand()- Select region with mouse MEX - MATLAB Executable • Dynamically linked subroutines produced from C, C++ or Fortran source code. • Useful when dealing with non efficient-Matlab algorithms (e.g. iterative algorithm implemented as loops). • mex –setup : Setup mex compiling configurations. Data Visualization Useful Commands: • scatter()/plot() – Useful to plot points on image. • imagesc() – Useful for 2D data. • print() – Save figure as image on disk (careful with lossy compressions) General Tips • Avoid loops • Manage memory (Clear unused variables) • Useful command: clearvars() • Avoid memory duplication – use nested functions function myfun A = magic(500); function setrowval(row, value) A(row,:) = value; end setrowval(400, 0); disp('The new value of A(399:401,1:10) is') A(399:401,1:10) end General Tips • Avoid memory duplication – don’t want to use nested functions? Simply use the same variable name: function x = demo x=rand(10000); x=func(x); function a=func(a) a=a*2; General Tips • Preallocating Arrays tic x = 0; for k = 2:1000000 x(k) = x(k-1) + 5; end toc Elapsed time is 0.301528 seconds. tic x = zeros(1, 1000000); for k = 2:1000000 x(k) = x(k-1) + 5; end toc Elapsed time is 0.011938 seconds. • Preallocate correctly A = int8(zeros(100)); A = zeros(100, 'int8'); General Tips • You will be amazed of the variety of built in functions that Matlab offers. • In fact, assume that the function you need is built in Matlab. It’s probably true! • Use Matlab “help” to understand how to use functions • Use Google to search for new functions! General Tips Long-Term Usage (Windows Systems Only) On 32-bit Microsoft Windows, the workspace of MATLAB can fragment over time due to the fact that the Windows memory manager does not return blocks of certain types and sizes to the operating system. Clearing the MATLAB workspace does not fix this problem. You can minimize the problem by allocating the largest variables first. This cannot address, however, the eventual fragmentation of the workspace that occurs from continual use of MATLAB over many days and weeks, for example. The only solution to this is to save your work and restart MATLAB. The pack command, which saves all variables to disk and loads them back, does not help with this situation. Tricks Stenography (Wikipedia) The art of hiding a message within another larger message Original Result Tricks Stenography (Wikipedia) The art of hiding a message within another larger message I= imread('StenographyOriginal.png'); I4=85*mod(I,4); figure; subplot(1,2,1) imshow(I); title('Original'); subplot(1,2,2) imshow(I4);title('Result'); Tricks Almost Connected (Steve Eddins’ Blog) Tricks Almost Connected (Steve Eddins’ Blog) url = 'http://blogs.mathworks.com/images/steve/2010/blobs_in_clumps.png'; bw = imread(url); lbl = bwlabel(bw); figure; imagesc(lbl); axis image; 50 100 150 200 250 300 50 100 150 200 250 300 Tricks Almost Connected (Steve Eddins’ Blog) bw2 = bwdist(bw) <= 12.5; lbl2 = bwlabel(bw2); figure; imshow(bw2); figure; imagesc(lbl2); axis image; 50 100 150 200 250 300 50 100 150 200 250 300 Tricks Almost Connected (Steve Eddins’ Blog) lbl3 = lbl2.*bw; figure; imagesc(lbl3); axis image; 50 100 150 200 250 300 50 100 150 200 250 300 Tricks Feature AND (Steve Eddins’ Blog) bw = imread('text.png'); dots = rand(size(bw))>0.99; Tricks Feature AND (Steve Eddins’ Blog) touching_pixels = bw & dots; Overlapping Tricks Feature AND (Steve Eddins’ Blog) out = imreconstruct(touching_pixels, bw); Reconstructed Of course this will work just as well: out = imreconstruct(dots, bw);