No self-introduction
Loading
Profile
Follow
codes (6)
Fusion weighted averaging method for gray or color
no vote
Application background Using weighted average fusion algorithm for gray or color multi modality medical image fusion, the program is very good, and provides several image fusion objective evaluation index, and the 3 groups of valuable registered images
gongsunze 0 0
1
The mutation of genetic algorithm is introduced in
no vote
Application background For intelligent computation and optimization theory, genetic algorithm and particle swarm algorithm are modern bionic optimization algorithm, but both are different, the core of the genetic algorithm is that the mutation and crossover, the core of the particle swarm algorithm is that individual search optimization and group optimization balance. Usually study machinery will combine the two algorithms, which makes the program more complex, operation time too long. This program mainly by the particle swarm optimization algorithm, cleverly will thought of variation of genetic algorithm was introduced to particle swarm optimization algorithm, the improved simple can greatly improve the performance of particle swarm optimization algorithm. However, the threshold for the introduction of a random number needs to be determined by repeated experiments. Key Technology Will thought of variation of genetic algorithm skillful applicatio
gongsunze 9 0
1
Using ICA method, 3 images are separated from the
no vote
Application background For actual sometimes collected image contains several independent components (sub images), these components even overlap together, then you can use ICA methods they were isolated. In order to test the program, the first three separate images are mixed together, and then the use of blind signal processing ICA technology to all of them separated out, the effect is not bad. There are pictures, you can run directly Key Technology ICA technology, independent component analysis, blind signal processing, one of the key technologies, a few of the prior knowledge requirements, and even no, PCA hypothesis is a high dataThe exponential distribution, while the ICA assumes that the data are independent of each other. So inIn the actual processing, ICA is better in small sample set, but for large sample set, PCACan also achieve good results. Obviously, ICA is more suitable for only a few independent components (or sub images).
gongsunze 0 0
1
The difference of 3 typical display function of MA
no vote
Application background Test to see matlab three display function image, imshow and imagesc difference. First discuss the image storage format of image processing, showed no effect, then the image of R, G, B, respectively, show, integration, intuitively show the three display function differences, including image, can be directly run the show Key Technology R, G, B three channels are displayed, processing images, suitable for beginners image processing, to clarify the basic issues, the master can be ignored
gongsunze 1 0
1
Color image magnification and sharpening
no vote
Color image size increases, and deblurring. The use of the RGB to HSI conversion model, operation of the I component, call the imresize function... Using 4 kinds of Laplasse operator template, typical in sharpening, smoothing,... In the recovery to RGB model.
gongsunze 0 0
1
A general algorithm for image restoration Wiener f
no vote
The Bitu noise variance a dropped by 5 orders of magnitude of the contaminated image Wiener filter, with the typical noise types are available, there are more detailed notes, suitable for beginners who study image processing
gongsunze 1 0
1
No more~
Follows0
Fans0