## Matlab7.x image processing functions

GDI-Bitmap     Matlab

Matlab7.x image processing
ch2_1_1: histogram (§ 2.1.3)
ch2_2_1: display images (§ 2.2.2)
ch2_3_1: Add a color bar (§ 2.3.1)
ch2_3_2: a single frame of the image display (§ 2.3.2)
ch2_3_3: multi-frame image display (§ 2.3.2)
ch2_3_4: image animation (§ 2.3.2)
ch2_3_5: the animated display of grayscale images (§ 2.3.2)
ch2_3_6: Texture Mapping (§ 2.3.3)
ch2_3_7: a graphical window to display two images (§ 2.3.4)
ch3_1_1: nested image algebra function (§ 3.1.1)
ch3_1_2: the two images is the sum of (§ 3.1.2)
ch3_1_3: image and constant sum (§ 3.1.2)
ch3_1_4: two image subtraction (§ 3.1.3)
ch3_1_5: two images by multiplying (§ 3.1.4)
ch3_1_6: the image is divided by a constant (two images divided by) (§ 3.1.5)
ch3_2_1: image scaling (§ 3.2.2)
ch3_2_2: image rotation (§ 3.2.3)
ch3_2_3: image shear (§ 3.2.4)
ch3_2_4: generation and application of an affine transformation (§ 3.2.5)
ch3_2_5: findbounds function of the application (§ 3.2.5)
ch3_2_6: makeresampler function of the application (§ 3.2.5)
ch3_2_7: the projection transformation (§ 3.2.5)
ch3_3_1: to calculate the image of local standard deviation (§ 3.3.1)
ch3_3_2: Calculate the maximum of the 3 × 3 neighborhood pixel values of the input image (§ 3.3.2)
ch3_4_1: according to the specified coordinates for a hexagonal region (§ 3.4.1)
ch3_4_2: segmentation by gray level image of the target (§ 3.4.1)
ch3_4_3: function poly2mask the call format (§ 3.4.1)
ch3_4_4 Sharpen filter (§ 3.4.2): a designated area
ch3_4_5: Fill a designated area (§ 3.4.3)
ch4_1_1: rectangular Fourier transform of the continuous function (§ 4.1.1)
ch4_1_2: to build a rectangular function (§ 4.1.2)
ch4_1_3: two-dimensional fast Fourier transform (§ 4.1.2) for f
ch4_1_4 zeros: f (area size of 256 × 256), then two-dimensional fast Fourier transform (§ 4.1.2)
ch4_1_5: transform the results of the zero-frequency component in the center, call the function fftshift (§ 4.1.2)
ch4_1_6: function ifft2 the product of the inverse Fourier transform (§ 4.1.3)
ch4_1_7: positioning results (§ 4.1.3) corresponds to the letter "a" in the image text.png
ch4_2_1: an image discrete cosine transform (§ 4.2.1)
ch4_2_2: the JPEG image compression (§ 4.2.2)
ch4_3_1: square image in the direction of 0 ° and 45 ° on the Radon transform (§ 4.3.1)
ch4_3_2: Calculate the square image from 0 ° to 180 ° every 1 ° calculation of the Radon transform command (§ 4.3.1)
ch4_3_3: line detection (§ 4.3.1)
ch4_3_4: use the radon function and iradon of function to construct a simple image projection and reconstructed images (§ 4.3.2)
ch4_4_1: mapping and reconstruction of images (§ 4.4.1)
ch5_1_1: image gray linear transformation (§ 5.1.1)
ch5_1_2: image gray piecewise linear transformation (§ 5.1.1)
ch5_1_3: the transfer function of the number of forms of dynamic range compression (§ 5.1.1)
ch5_1_4: histogram equalization (§ 5.1.2)
ch5_1_5: histogram specification (§ 5.1.2)
ch5_2_1: neighborhood average linear smoothing filter method noise (§ 5.2.2)
ch5_2_2: winner filtering method to achieve the noise reduction (§ 5.2.2)
ch5_2_3: Median filtering noise reduction (§ 5.2.2)
ch5_2_4: Linear Sharpen filter (§ 5.2.3)
ch5_2_5: sharp non-linear filtering (§ 5.2.3)
ch5_3_1: Buterworth low-pass filter (§ 5.3.1)
ch5_3_2: Buterworth high-pass filter (§ 5.3.2)
ch5_4_1: gray-scale layering color images to achieve (§ 5.4.2)
ch5_4_2: spatial domain grayscale - color transform, image enhancement (§ 5.4.2)
ch5_4_3: mean filter for true color images for each color plane filter (§ 5.4.3)
ch5_5_1: noise image generation (§ 5.5.4)
ch5_5_2: target image generation (§ 5.5.4)
ch6: Huffman coding (§ 6.1.4)
ch7_1_1: The maximum variance method to calculate the gray level segmentation threshold (§ 7.1.2)
ch7_1_2: a variety of edge detection operator (§ 7.2.2)
ch7_2_1: Hough transform line detection (§ 7.2.3)
ch7_2_2.: Phase Classification (§ 7.2.3)
ch8_3_1: blurred images (§ 8.3.2)
ch8_3_2: the original image, add noise (§ 8.3.2)
ch8_4_1: Generate fuzzy of experimental images (§ 8.4.1)
ch8_4_2: Wiener filter restoration (§ 8.4.2)
ch8_4_3: constrained least squares filtering for restoration (§ 8.4.3)
ch8_4_4: Lucy-Richardson filter restoration (§ 8.4.4)
ch8_4_5: Blind convolution filter restoration (§ 8.4.5)
ch9_2_1: call bwmorph function of the skeleton of operation (§ 9.2.4)
ch9_2_2: function bwperim to extract the boundary operation (§ 9.2.4)
ch9_2_3: using function bwmorph achieve the extraction of the operation of the border and skeleton of operation (§ 9.2.4)
ch9_2_4: use function imbothat image processing (§ 9.2.4)
ch9_2_5: the function imclose perform image closing operation (§ 9.2.4)
ch9_2_6: the function imopen implementation of the image to open computing degree (§ 9.2.4)
ch9_2_7: use function imtophat enhance the image contrast (§ 9.2.4)
ch9_3_1: Generate consists of two main local minimum region and several other local minima region (§ 9.3.4)
ch9_4_1: distance transform (§ 9.4)
ch9_5_1: function label2rgb call each object is displayed as different colors (§ 9.5.1)
ch9_5_2: Extract certain characters in the text in the image object (§ 9.5.2)
ch9_5_3: function bwarea calculation the percentage of the expansion area of growth after the operation performed on the image (§ 9.5.3)
ch9_5_4: function bweuler the Euler number calculation (§ 9.5.4)
ch9_6_1: the call the function makelut applylut to achieve the look-up table operations (§ 9.6)
ch10_1_1: using function imfilter image filtering (§ 10.1.3)
ch10_2_1: use of frequency transformation method to generate a 2-D filter (§ 10.2.2)
ch10_2_2: the use of the frequency sampling method to generate a 2-D filter (§ 10.2.3)
ch10_2_3: window method to generate a 2-D filter (§ 10.2.4)
ch10_2_4: a design for the 0.5 is an ideal low-pass filter cutoff frequency (§ 10.2.5)

#### Project Files

```NameSizeDate
ch2_1_1.m49.00 B02-06-06 16:15
ch2_2_1.m47.00 B02-06-06 16:16
ch2_3_1.m146.00 B29-05-06 23:31
ch2_3_2.m210.00 B29-05-06 23:35
ch2_3_3.m145.00 B29-05-06 23:40
ch2_3_4.m168.00 B29-05-06 23:41
ch2_3_5.m151.00 B02-06-06 16:24
ch2_3_6.m62.00 B02-06-06 16:24
ch2_3_7.m118.00 B02-06-06 16:25
ch3_1_1.m87.00 B02-06-06 16:26
ch3_1_2.m93.00 B02-06-06 16:27
ch3_1_3.m99.00 B02-06-06 16:27
ch3_1_4.m86.00 B02-06-06 16:28
ch3_1_5.m106.00 B02-06-06 16:28
ch3_1_6.m104.00 B02-06-06 16:29
ch3_2_1.m176.00 B02-06-06 16:30
ch3_2_2.m90.00 B02-06-06 16:30
ch3_2_3.m84.00 B02-06-06 16:30
ch3_2_4.m137.00 B02-06-06 16:31
ch3_2_5.m164.00 B02-06-06 16:34
ch3_2_6.m547.00 B02-06-06 16:35
ch3_3_1.m222.00 B02-06-06 16:35
ch3_3_2.m113.00 B02-06-06 16:37
ch3_3_3.m120.00 B02-06-06 16:38
ch3_4_1.m139.00 B02-06-06 16:38
ch3_4_2.m85.00 B02-06-06 16:39
ch3_4_3.m140.00 B02-06-06 16:40
ch3_4_4.m240.00 B03-06-06 01:33
ch3_4_5.m137.00 B02-06-06 16:41
ch4_1_1.m193.00 B02-06-06 16:41
ch4_1_2.m63.00 B02-06-06 16:42
ch4_1_3.m90.00 B02-06-06 16:42
ch4_1_4.m80.00 B02-06-06 16:43
ch4_1_5.m98.00 B02-06-06 16:43
ch4_1_6.m156.00 B03-06-06 01:34
ch4_1_7.m213.00 B02-06-06 23:03
ch4_2_1.m196.00 B02-06-06 23:04
ch4_2_2.m623.00 B02-06-06 23:05
ch4_3_1.m188.00 B02-06-06 23:05
ch4_3_2.m240.00 B02-06-06 23:06
ch4_3_3.m176.00 B02-06-06 23:07
ch4_3_4.m180.00 B02-06-06 23:07
ch4_3_5.m623.00 B30-05-06 00:02
ch4_4_1.m1.82 kB30-05-06 00:05
ch5_1_1.m593.00 B02-06-06 12:26
ch5_1_2.m601.00 B02-06-06 12:16
ch5_1_3.m418.00 B02-06-06 12:16
ch5_1_4.m312.00 B02-06-06 12:34
<ch5_1_5>0.00 B75% 02-06-06
ch5_2_1.m401.00 B02-06-06 12:23
<ch5_2_2>0.00 B74% 02-06-06
ch5_2_3.m359.00 B02-06-06 12:35
ch5_2_4.m331.00 B02-06-06 12:17
ch5_2_5.m829.00 B02-06-06 12:25
ch5_3_1.m502.00 B02-06-06 12:15
ch5_3_2.m463.00 B02-06-06 12:15
ch5_4_1.m269.00 B02-06-06 12:15
ch5_4_2.m505.00 B02-06-06 12:17
ch5_4_3.m438.00 B02-06-06 12:33
ch5_5_1.m601.00 B02-06-06 12:21
ch5_5_2.m1.01 kB02-06-06 12:21
ch6.m5.08 kB03-06-06 13:41
ch7_1_1.m810.00 B01-06-06 20:30
ch7_2_1.m457.00 B01-06-06 17:35
ch7_2_2.m2.23 kB01-06-06 20:33
ch7_2_3.m3.15 kB01-06-06 20:44
ch8_3_1.m491.00 B30-05-06 00:08
ch8_3_2.m379.00 B30-05-06 00:08
ch8_4_1.m682.00 B30-05-06 00:10
ch8_4_2.m2.31 kB30-05-06 00:15
ch8_4_3.m1.04 kB30-05-06 00:19
ch8_4_4.m295.00 B30-05-06 00:23
ch8_4_5.m901.00 B30-05-06 00:21
ch9_2_1.m96.00 B03-06-06 01:14
ch9_2_2.m85.00 B03-06-06 01:15
ch9_2_3.m196.00 B30-05-06 00:25
ch9_2_4.m136.00 B03-06-06 01:15
ch9_2_5.m134.00 B03-06-06 01:16
ch9_2_6.m112.00 B03-06-06 01:16
ch9_2_7.m100.00 B03-06-06 01:17
ch9_3_1.m147.00 B03-06-06 01:18
ch9_4_1.m486.00 B30-05-06 00:27
ch9_5_1.m82.00 B03-06-06 01:19
ch9_5_2.m118.00 B03-06-06 01:19
ch9_5_3.m119.00 B03-06-06 01:20
ch9_5_4.m52.00 B03-06-06 01:20
ch9_6_1.m112.00 B03-06-06 01:21
ch10_1_1.m185.00 B30-05-06 00:29
ch10_2_1.m232.00 B30-05-06 00:30
ch10_2_2.m216.00 B30-05-06 00:31
ch10_2_3.m615.00 B03-06-06 01:39
ch10_2_4.m116.00 B03-06-06 01:24
程序说明.doc46.50 kB18-09-06 13:20
<chap02>0.00 B09-07-09 02:44
<chap03>0.00 B09-07-09 02:44
<chap04>0.00 B09-07-09 02:44
<chap05>0.00 B09-07-09 02:44
<chap06>0.00 B09-07-09 02:44
<chap07>0.00 B09-07-09 02:44
<chap08>0.00 B09-07-09 02:44
<chap09>0.00 B09-07-09 02:44
<chap10>0.00 B09-07-09 02:44
<code>0.00 B09-07-09 02:44

...```

#### Related Items

1. Prim algorithms for minimum spanning tree (MST)(Algorithm - C++) - A good Prim method of MST programs ...
2. MaximumSpanningTree.(Windows Develop - Matlab) - kruskal minimum spanning tree kruskal minimum spanning tree ...
3. prefixspan-0.1.tar.g(AI-NN-PR - Visual C++) - Classical data association mining algorithm PrefixSpan ...
4. minimumspanningtree.(Windows Develop - Visual C++) - Given a connected weighted undirected graph, find the minimu ...
5. span_forest.rar(Data structs - C++) - Computes estimates for the number of fores ts of a graph. in ...
6. PrefixSpan.rar(AI-NN-PR - Java) - PrefixSpan algorithm. The document containing a detailed des ...
7. LowLevelDriver4spans(Embeded-SCM Develop - Visual C++) - spansion flash underlying driver code ...
8. MiniSpanTree.rar(Data structs - Visual C++) - I have written a C++ Kruskal minimum spanning tree procedure ...
9. SpanningTree.rar(Data structs - Visual C++) - First construct a map with the adjacency matrix is stored se ...
10. ParMol_1346_2006-08-(Windows Develop - Others) - ParMol consists of the four graph miners MoFa, gSpan, FFSM a ...
11. Mass short message sender codes (Java)(Java Develop - Java) - SMS marketing platform, which includes bulk SMS, SMS sending ...
12. English-Spanishwordt(Other windows programs - VB) - English-Spanish word translation, and a word memory test fun ...
13. prefixspan-0.4-ngram(AI-NN-PR - Visual C++) - ...
14. edmonds-alg-0.9.0.ta(Data structs - Visual C++) - Directed graph in calculating minimum spanning tree--- Edmon ...
15. mapminimumspanningtr(Data structs - C++) - algorithm commonly used data structures : Figure the minimum ...
16. PrefixSpanMiningeque(Document - Matlab) - Sequential pattern mining algorithm PrefixSpan documents, ve ...
17. sssss.rar(Delphi VCL - Others) - skin button skinbutton transpanel welcome improvement ...
18. minimumspanningtree.(Windows Develop - Visual C++) - minimum spanning tree. Rar ...
19. minimumspanningtree1(Data structs - VB) - this procedure is a prim with minimum spanning tree algorith ...
20. minimumspanningtree((Windows Develop - Borland C++ Builder) - procedures with the greedy algorithm to solve the problem us ...