image proccessing and its applications
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IMAGE PROCESSING AND IMAGE
COMPRESSING
BY ASHWINI AWATARE
Contents:-What is Image Processing ?Steps followed in Image Processing .Purpose of Image Processing.Types of Image Processing Applications of Image Processing Advantage and Limitations .Image Compression Goals of Image Compression .Flow of Image Compression.ApproachesModels
What is Image Processing Image processing is a method to convert an
image into digital form and perform some operations on it, in order to get an enhanced image or to extract some useful information from it.
Usually Image Processing system includes treating images as two dimensional signals while applying already set signal processing methods to them.
Image Processing :An image defined in the "real world" is considered to bea function of two real variables say x , y. Before going to processing an image, it is converted intoa digital form. Digitization includes sampling of imageand quantization of sampled values. After converting the image into bit information,
processing is performed.This processing technique may be,
*Image enhancement* Image reconstruction* Image compression
Image enhancement refers to accentuation, or sharpening, of image features such as boundaries.
Image restoration is concerned with filtering the observed image to minimize the effect of degradations.
Image compression is concerned with minimizing the number of bits required to represent an image. * Text compression - CCITT GROUP3 & GROUP4 * Still image compression - JPEG * Video image compression -MPEG
Image processing basically includes the following three steps. Importing the image with optical scanner or
by digital photography.Analyzing and manipulating the image which
includes data compression and image enhancement and spotting patterns that are not to human eyes like satellite photographs.
Output is the last stage in which result can be altered image or report that is based on image analysis.
Modern digital technology has made it possible to manipulate multi-dimensional signals with systems that range from simple digital circuits to advanced parallel computers. The goal of this manipulation can be divided into three categories:
* Image Processing image in -> image out * Image Analysis image in -> measurements out * Image Understanding image in -> high-level description out
Image processing is referred to processing of a 2D picture by a computer.
Purpose of Image processingThe purpose of image processing is divided into 5
groups. They are: Visualization - Observe the objects that are not
visible. Image sharpening and restoration - To create a
better image. Image retrieval - Seek for the image of interest. Measurement of pattern – Measures various
objects in an image. Image Recognition – Distinguish the objects in
an image.
Types of Image Processing There are two types of the Image Processing
1> Analog Image Processing Analog Image Processing refers to the alteration of image through electrical means. The most common example is the televisionimage.
2>Digital Image Processing :In this case, digital computers are used toprocess the image. The image will be converted to digital form
using a scanner – digitizer and then process it.
It is defined as the subjecting numerical representations of objects to a series of operations in order to obtain a
desired result
Applications :Computer Vision Agricultural Applications Face DetectionMedical Imaging Microscope Image Processing Raster Operation Remote Sensing Non-destructive Evaluation
Applications Forensic Studies Textiles Material Science. Military Film industry Document processing Graphic arts Printing Industry
Advantage Advantages are as follows :
you can remove unwanted objects, adjust exposure, saturation, hue, levels, sharpness, and more.
Easy to manipulate. Compact storage.
Limitations :-Limitations are as follows:
It's very costly depending on the system used, the number of detectors purchased.
Time consuming Lack of qualified professional
Image Compression :-The objective of image compression is to
reduce irrelevance and redundancy of the image data in order to be able to store or transmit data in an efficient form.
Image compression is minimizing the size in bytes of a graphics file without degrading the quality of the image to an unacceptable level. The reduction in file size allows more images to be stored in a given amount of disk or memory space
It also reduces the time required for images to be sent over the Internet or downloaded from Web pages.
There are several different ways in which image files can be compressed. For Internet use, the two most common compressed graphic image formats are the JPEG format and the GIF format. The JPEG method is more often used for photographs, while the GIF method is commonly used for line art and other images in which geometric shapes are relatively simple.
The JPEG standard specifies the codec, which defines how an image is compressed into a stream of bytes and decompressed back into an image, but not the file format used to contain that stream.
The Exif and JFIF standards define the commonly used file formats for interchange of JPEG-compressed images.
Goal of Image CompressionThe goal of image compression is to reduce
the amount of data required to represent a digital image.
The Flow of Image Compression
What is the so-called image compression coding?
To store the image into bit-stream as compact as possible and to display the decoded image in the monitor as exact as possible
Flow of compressionThe image file is converted into a series of binary data, which is called the bit-streamThe decoder receives the encoded bit-stream and decodes it to reconstruct the imageThe total data quantity of the bit-stream is less than the total data quantity of the original image
Encoder 0101100111... Decoder
Original Image Decoded ImageBitstream
ApproachesLossless
Information preservingLow compression ratios
LossyNot information preservingHigh compression ratios
Definitions: Compression Ratio
compression
Compression ratio:
Image Compression Model
Image Compression Model
Mapper: transforms input data in a way that facilitates reduction of interpixel redundancies.
Image Compression Model
Quantizer: reduces the accuracy of the mapper’s output in accordance with some pre-established fidelity criteria.
Image Compression Model
Symbol encoder: assigns the shortest code to the most frequently occurring output values.
Image Compression Models
Inverse steps are performed.
Note that quantization is irreversible in general.
Sources :
http://www.noupe.com/design/everything-you-need-to-know-about-image-compression.html
http://en.wikipedia.org/wiki/Image_processing
http://en.wikipedia.org/wiki/Image_compression
http://whatis.techtarget.com/definition/image-compression
http://www.html5rocks.com/en/tutorials/speed/img-compression/
http://docs.gimp.org/en/gimp-tutorial-quickie-jpeg.html // jpeg image compression .
THANK YOU
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