Image processing is the technique to convert an image into digital format and perform operations on it
to get an enhanced image or extract some useful information
1=imread()command will read an image into a matrix:
2=imshow()command displays the image on scaled axes (To show our image)
3=imwrite()Write the Adjusted Image to a Disk File To save your new
image
4=rgb2gray() converted RGB images to grayscale by eliminating the hue and saturation information
while retaining the luminance.
5=imhist() Display a histogram of image data.
6=imadjust() adjust image intensity
This increases the contrast of the output image.
7=im2bw() converts the grayscale image to a binary image.
8=imfinfo
9=ind2gray
luminance
removes the hue and saturation information from the input image while retaining the
10=im2bw() grayscale image I to binary image BW
11=BW=edge()
12= imroatate
gray level adjustment
a) identity transformation= each value of the image is directly mapped to output image
Negative transformation = each value of input image is subtracted from L-1 and then it is mapped onto
output image.
b) log tranformation = s = c log(r + 1) Log transformation means replacing each pixel value with its
logarithm value. (Used to expand values of dark pixels in an image while compressing the
higher-level values).
C) POWER LAW =This type of transformation is used for enhancing images for different type of display
devices. The gamma of different display devices is different
Gamma correction function is a function that maps luminance levels to compensate the non-linear
luminance effect of display devices
bit plane slicing is:
Converting a gray level image to a binary image.
Representing an image with fewer bits and to a smaller size
Enhancing the image by focussing.
The Median Filter is a non-linear digital filtering technique,
signal
used to remove noise from an image or
Salt-and-pepper noise = can be caused by sharp and sudden disturbances in the image signal
white and black pixels
Adaptive filters are used in image processing to enhance or restore data by removing noise without
blurring structures in the image
Gaussian Noise is a statistical noise having a probability density function equal to normal distribution,
also known as Gaussian Distribution
The probability distribution function, P(a), is the probability that a brightness
Prewitt operator is used for edge detection in an image. It detects two types of edges
Horizontal edges
Vertical Edges
by using difference between corresponding pixel intensities of an image
SOBEL OPREATOR difference is that coefficent of mask adjusted according to our requirement
Skeletonization is a process for reducing foreground regions in a binary image to a skeletal texture