what is an image and how to process an image according to human needs. Compression of image to different formats.

1. IMAGE
PROCESSING
&
COMPRESSION

2. WHAT IS AN IMAGE?
• Image processing is done to enhance an existing image or to sift out important information from it. This is
important in several Deep Learning-based Computer Vision applications, where such preprocessing can
dramatically boost the performance of a model. Manipulating images, for example, adding or removing objects to
images, is another application, especially in the entertainment industry.

3. TYPES
• mainly FIVE types of image processing:
• Visualization - Find objects that are not visible in the image
• Recognition - Distinguish or detect objects in the image
• Sharpening and restoration - Create an enhanced image from the original image
• Pattern recognition - Measure the various patterns around the objects in the image
• Retrieval - Browse and search images from a large database of digital images that are
similar to the original image

4. FUNDAMENTAL STEPS IN DIGITAL IMAGE
PROCESSING :
• 1. Image Acquisition
• This is the first step or process of the fundamental steps of digital image processing. Image acquisition could be
as simple as being given an image that is already in digital form. Generally, the image acquisition stage involves
preprocessing, such as scaling etc.
• 2. Image Enhancement
• Image enhancement is among the simplest and most appealing areas of digital image processing. Basically, the
idea behind enhancement techniques is to bring out detail that is obscured, or simply to highlight certain features
of interest in an image. Such as, changing brightness & contrast etc.
• 3. Image Restoration
• Image restoration is an area that also deals with improving the appearance of an image. However, unlike
enhancement, which is subjective, image restoration is objective, in the sense that restoration techniques tend to
be based on mathematical or probabilistic models of image degradation.

5. • Color Image Processing
• Color image processing includes a number of color modeling techniques in a digital domain. This step has gained prominence due to
the significant use of digital images over the internet.
• Wavelets and Multiresolution Processing
• Wavelets are used to represent images in various degrees of resolution. The images are subdivided into wavelets or smaller regions
for data compression and for pyramidal representation.
• Compression
• Compression is a process used to reduce the storage required to save an image or the bandwidth required to transmit it. This is done
particularly when the image is for use on the Internet.
• Morphological Processing
• Morphological processing is a set of processing operations for morphing images based on their shapes.

6. APPLICATIONS OF IMAGE PROCESSING
• The digital image can be made available in any desired format (improved image, X-Ray, photo
negative, etc)
• It helps to improve images for human interpretation
• Information can be processed and extracted from images for machine interpretation
• The pixels in the image can be manipulated to any desired density and contrast
• Images can be stored and retrieved easily
• It allows for easy electronic transmission of images to third-party providers

7. IMAGE COMPRESSION
• Image files may be too big for network transmission, even at low
resolutions.
• Use more sophisticated data representation or discard information to
reduce data size.
• Effectiveness of compression will depend on actual image data.

8. COMPRESSION STEPS
• 1. Preparation: analog to digital conversion.
• 2. Processing: transform data into a domain easier to compress.
• 3. Quantization: reduce precision at which the output is stored.
• 4. Entropy encoding: remove redundant information in the resulting data stream.
Picture
Preparation
Picture
Processing
Quanti-
zation
Entropy
Encoding
Image
Uncompressed
Image
Compressed

9. IMAGE PREPARATION
• In the first step of an image compression process the
images are prepared for the actual processing.
• Image Preparation in JPEG (components):
Components at the image preparing state of JPEG may be
assigned, for example, to the different colors in RGB
(red, green, blue
• A gray-scale image will, in most cases, consist of a single
component. An RGB color representation has three
components with the same number of lines and the same
number of columns.
• the image is represented in n (0 < n < 256) components.
Each component consists of an array of pixels.

10. PROCESSING:
• The second step of an image compression process, a transformation is applied to the
prepared data.
Image Processing in JPEG:
•
For the decompression of the JPEG coded data the inverse DCT (discrete cosine
transform )must be applied to get a presentation of the time space.
•

11. IMAGE COMPRESSION:
QUANTIZATION:
The quantization
In the JPEG process is a lossy transformation.
The 64 coefficients obtained from the DCT step are quantized with a table with 64 entries. Each coefficient
can be adjusted separately.
Therefore, the relative significance of the different coefficients can be influenced and specific frequencies
can be given more importance than others.

12. IMAGE COMPRESSION: ENTROPY ENCODING:
• In the fourth step of an image compression process an entropy encoding(a way of lossless compression
that is done on an image after the quantization stage) is applied to the quantized coefficients.
• quantization process of mapping continuous infinite values to a smaller set of discrete finite values
• To reduce the amount of data lossless processes can be used. These methods make use exclusively of the
redundancy of the data.
• Processes with this principle are called entropy encoding. There are several of this kind. Entropy encoding is used
regardless of the media’s specific characteristics.
• The data stream to be compressed is considered to be a simple digital sequence, and the semantic of the data is
ignored. Entropy encoding is an example of lossless encoding as the decompression process regenerates the data
completely. The raw data and the decompressed data are identical, no information is lost.

13. APPLICATIONS
• Lossy Compression and Lossless compression methods are used. selection of a method to compress
images depends on the quality of the output that is expected by the users. When a very high quality
output is expected without any loss of data by users from image compression applications then lossless
compression technique can be used by the application.
• lossy compression technique where the quality is not that much important.
• It can be used in such applications where a little compromise on quality of image is tolerable.
• The areas where image compression is used are in television broadcasting, Remote sensing via
satellite, for military communication systems through radars, Tele conferencing systems,
communications systems built through computers, capturing and transmitting satellite images,
geological surveys, weather reporting

14. GROUP 12
ADNAN
NOOHU
RASHIN
SAROON