Programming Homework
HWP2: Counting Pixels with Histograms
Goal: Histogram processing for image enhancement
Goal: Histogram processing for image enhancement
- Know how to enhance image by histogram processing
- Apply look-up table to enhance images
- Learn histogram equalization, histogram backpropagation, and mean shift
- Practice image retrieval by histogram matching.
Readings and sample codes
Readings and sample codes
Web Report
Web Report
- Create a web page with description texts and a lot of pictures for the following programs
- histogram.cpp: (1) Computing the image histogram. (2) Equalize the image. (3) Applying Look-up Tables to Modify Image Appearance. (p.106, p.107, p.112, p.114, p.116, p.117 in PDF)
- Change the image and the look-up tables to practice this sample code.
- contentfinder.cpp: Backprojecting a Histogram to Detect Specific Image Content. (p.118, p.120, p.124 in PDF).
- Change images with blue sky or green grass to get your results.
- finder.cpp: Using the Mean-shift Algorithm to Find an Object. (p.126, p.128 in PDF).
- Change the image with persons and use human's face as the target to apply mean-shot algorithm.
- retrieve.cpp: Retrieving Similar Images using Histogram Comparison (p.132 in PDF)
- Collect a set of images with "similar colors". Use one image as query image, all the other images as gallary images. Retrieve similar image of the query from the gallery.
- integral.cpp: Create a binary image by adaptively setting a threshold. (p.140 in PDF)
- tracking.cpp: Locate an object in the image. (p.144 in PDF)
- histogram.cpp: (1) Computing the image histogram. (2) Equalize the image. (3) Applying Look-up Tables to Modify Image Appearance. (p.106, p.107, p.112, p.114, p.116, p.117 in PDF)
- You have to give explanations of the codes. And you have to identify how did you modify the source code to get your results.
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