User manual MATLAB VIDEO AND IMAGE PROCESSING BLOCKSET 3

[. . . ] Video and Image Processing BlocksetTM 3 User's Guide How to Contact The MathWorks Web Newsgroup www. mathworks. com/contact_TS. html Technical Support www. mathworks. com comp. soft-sys. matlab suggest@mathworks. com bugs@mathworks. com doc@mathworks. com service@mathworks. com info@mathworks. com Product enhancement suggestions Bug reports Documentation error reports Order status, license renewals, passcodes Sales, pricing, and general information 508-647-7000 (Phone) 508-647-7001 (Fax) The MathWorks, Inc. 3 Apple Hill Drive Natick, MA 01760-2098 For contact information about worldwide offices, see the MathWorks Web site. Video and Image Processing BlocksetTM User's Guide © COPYRIGHT 2004­2010 by The MathWorks, Inc. The software described in this document is furnished under a license agreement. The software may be used or copied only under the terms of the license agreement. [. . . ] Open the Configuration dialog box by selecting Configuration Parameters from the Simulation menu. Set the parameters as follows: · Solver pane, Stop time = 0 · Solver pane, Type = Fixed-step · Solver pane, Solver = Discrete (no continuous states) 10 Run the model. The original noisy image appears in the Video Viewer window. To view the image at its true size, right-click the window and select Set Display To True Size. 4-43 4 Analysis and Enhancement The cleaner image appears in the Video Viewer1 window. The following image is shown at its true size. 4-44 Image Enhancement You have used the Median Filter block to remove noise from your image. For more information about this block, see the Median Filter block reference page in the Video and Image Processing Blockset Reference. Removing Periodic Noise from Video Periodic noise can be introduced into a video stream during acquisition or transmission due to electrical or electromechanical interference. In this example, you remove periodic noise from an intensity video using the 2-D FIR Filter block. You can use this technique to remove noise from other images or video streams, but you might need to modify the filter coefficients to account for the noise frequency content present in your signal: 1 Create a Simulink model, and add the blocks shown in the following table. 4-45 4 Analysis and Enhancement Block Read Binary File Image Data Type Conversion 2-D FIR Filter Video Viewer Add Library Video and Image Processing Blockset > Sources Video and Image Processing Blockset > Conversions Video and Image Processing Blockset > Filtering Video and Image Processing Blockset > Sinks Simulink > Math Operations Quantity 1 1 1 3 1 2 Open the Periodic noise reduction demo by typing vipstripes at the MATLAB command prompt. 3 Click-and-drag the Periodic Noise block into your model. The block outputs a sinusoid with a normalized frequency that ranges between 0. 61 and 0. 69 radians per sample and a phase that varies between zero and three radians. You are using this sinusoid to represent periodic noise. 4 Place the blocks so that your model resembles the following figure. The unconnected ports disappear when you set block parameters. 4-46 Image Enhancement You are now ready to set your block parameters by double-clicking the blocks, modifying the block parameter values, and clicking OK. 5 Use the Read Binary File block to import a binary file into the model. Set the block parameters as follows: · File name = cat_video. bin · Four character code = GREY · Number of times to play file = inf · Sample time = 1/30 4-47 4 Analysis and Enhancement 6 Use the Image Data Type Conversion block to convert the data type of the video to single-precision floating point. Accept the default parameter. 7 Use the Video Viewer block to view the original video. Accept the default parameters. 8 Use the Add block to add the noise video to the original video. Accept the default parameters. 9 Use the Video Viewer1 block to view the noisy video. Accept the default parameters. 10 Define the filter coefficients in the MATLAB workspace. Type the following code at the MATLAB command prompt: 4-48 Image Enhancement vipdh_stripes The variable h, as well as several others, are loaded into the MATLAB workspace. The variable h represents the coefficients of the band reject filter capable of removing normalized frequencies between 0. 61 and 0. 69 radians per sample. The coefficients were created using the Filter Design and Analysis Tool (FDATool) and the ftrans2 function. 11 Use the 2-D FIR Filter block to model a band-reject filter capable of removing the periodic noise from the video. Set the block parameters as follows: · Coefficients = h · Output size = Same as input port I · Padding options = Circular Choose a type of padding that minimizes the effect of the pixels outside the image on the processing of the image. In this example, circular padding produces the best results because it is most effective at replicating the sinusoidal noise outside the image. 4-49 4 Analysis and Enhancement 12 Use the Video Viewer2 block to view the approximation of the original video. Accept the default parameters. 13 Connect the block as shown in the following figure. 4-50 Image Enhancement 14 Set the configuration parameters. Open the Configuration dialog box by selecting Configuration Parameters from the Simulation menu. Set the parameters as follows: · Solver pane, Stop time = inf · Solver pane, Type = Fixed-step · Solver pane, Solver = Discrete (no continuous states) 15 Run the model. 4-51 4 Analysis and Enhancement The noisy video appears in the Video Viewer1 window. [. . . ] You can also set the display option directly via the MATLAB preferences dialog box. Select File > Preferences on the MATLAB desktop, and then select System Objects. Finally, select or deselect Show fixed-point properties. 10-6 Working with Fixed-Point Data If an object supports fixed-point data processing, its fixed-point properties are active regardless of whether they are displayed or not. Setting System Object Fixed-Point Properties A number of properties affect the fixed-point data processing used by a System object. Objects perform fixed-point processing and use the current fixed-point property settings when they receive fixed-point input. [. . . ]