Vladimir Botchko botchko@lut.fi

Preview:

DESCRIPTION

Lappeenranta University of Technology (Finland). Lecture 3. Image Enhancement in Spatial Domain. Vladimir Botchko botchko@lut.fi. Image Enhancement. Simple intensity transformations Histogram processing (equalization) Image subtraction Image averaging - PowerPoint PPT Presentation

Citation preview

1

Vladimir Botchko botchko@lut.fi

Lecture 3. Image Enhancement in Lecture 3. Image Enhancement in Spatial DomainSpatial Domain

Lappeenranta University of Technology (Finland)

2

Image Enhancement

Simple intensity transformations Histogram processing (equalization) Image subtraction Image averaging Spatial filtering (smoothing, sharpening) Enhancement. First derivative (gradient)

Example of manual edge enhancement: made by artist.

3

Simple intensity transformations

Contrast stretched

4

Simple intensity transformations

Intensity level slicing: Original image (top) Thresholded (left) Gray-level slicing (lower right)

5

Image Enhancement

Simple intensity transformations Histogram processing Image subtraction Image averaging Spatial filtering (smoothing, sharpening) Enhancement. First derivative (gradient).

6

Histogram equalization

7

Image Enhancement

Simple intensity transformations Histogram processing Image subtraction Image averaging Spatial filtering (smoothing, sharpening) Enhancement. First derivative (gradient).

8

Image subtraction

9

Image Enhancement

Simple intensity transformations Histogram processing Image subtraction Image averaging Spatial filtering (smoothing, sharpening) Enhancement. First derivative (gradient).

10

Image averaging. Spatial filtering (smoothing)

Original image (upper left) Original + noise (upper right) Smoothed image (lower right) Median smoothing (lower left)

11

Order-statistics filter for binary images (when numl=5 then it is

median) Rank filter is used for smoothing after recognition for segmentation. Simple Matlab

code is here:

12

Order-statistics filter

First is median filtering result (rank 5 for 3x3 window). Upper part is input image lower part is smoothed image

13

Order-statistics filter

Then the rank (rank 3 for 3x3 window). Original image upper, smoothed image is lower

14

Sharpening

Second Derivatives. Laplacian

15

Image Enhancement

Simple intensity transformations Histogram processing Image subtraction Image averaging Spatial filtering (smoothing, sharpening) Enhancement. First derivative (gradient).

16

Median filter and Sobel operator

Gray-level images (from left to right from top to bottom): original texture

synthetic (computer generated) image, the result of recognition corrupted by classification errors, median filtering, edge extraction through Sobel operator, superposition a gray level image and image with edges.