Tutorials on Digital Signal Processing - Free Video Lectures

1.Introduction to Digital Signal Processing
2.Introduction to Digital Signal Processing Contd
3.Digital Systems
4.Characterization Description,Testing of Digital Syst
5.LTI Systems Step & Impulse Responses,Convolution
6.Inverse Systems,Stability,FIR & IIR
7.FIR & IIR; Recursive & Non Recursive
9.Discrete Fourier Transform (DFT)
10.DFT (Contd.)
11.DFT (Contd.) and Introduction to Z Transform
12.Z Transform part1
13.Z Transform part2
14.Discrete Time Systems in the Frequency Domain
15.Simple Digital Filters
16.All Pass Filters,Com.Filters
17.Linear Phase filters,Complementary Transfer Fn
18.Compensatary Transfer Functions, (Contd.),
19.Test for Stability using All Pass Functions
20. Digital Processing of Continuous Time Signals
21. Problem Solving Session: FT, DFT,& Z Transforms
22. Problem Solving Session: FT,DFT, & Z Transforms
23. Analog Filter Design
24. Analog Chebyshev LPF Design
25. Analog Filter Design (Contd.): Transformations
26. Analog frequency Transformation;
27. Problem Solving Session on Discrete Time System
28. Digital Filter Structures
29. IIR Realizations
30. All Pass Realizations
31. Lattice Synthesis (Contd.)
32. FIR Lattice Synthesis
33. FIR Lattice (Contd.) and Digital Filter Design
34. IIR Filter Design
35. IIR Design by Bilinear Transformation
36. IIR Design Examples
37. Digital to Digital Frequency Transformation
38. FIR Design
39. FIR Digital Filter Design by Windowing
40. FIR Design by Windowing & Frequency Sampling
41. Solving Problems on DSP Structures
42. FIR Design by Frequency Sampling
43. FIR Design by Frequency Sampling (Contd.)
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JPEG Image Compression Explained

Topics Covered by title:

  • What is Compression?
  • Basic Need of Compression.
  • Types of Compression.
  • JPEG Encoder explained.

What is Compression?

Representing the data (Image, Audio, Video, Speech or Voice..) with the fewer number of bits than what it exactly requires to represent.

Basic Need of Compression
Effectively utilizing transmission bandwidth .Utilization of the storage media to the maximum.
Types of Compression:

  • Lossless Compressing the data which almost resembles the original Input data when decompressed.
  • Lossy Compressing the data with some lose of information(Keeping in mind of Human Visual and Psychoacoustic system) i.e. neglecting the higher frequency components which are very less sensitive to human visual system.
JPEG Image Compression standards.
In general image is nothing but a group of pixels. Pixel holds the brightness and color information of the image at a particular coordinate.
Red, Green and Blue are the primary color components of the color image.With the help of these color combinations we can get the color that we deserve.

Step by Step procedure in compressing input Image data.

  1. Input: Reading MxN (In general 8x8) block of input RGB Image each color component is of 8-bit.
  2. RBG->YcbCr: Converting MxN RBG samples to YCbCr (Luma and Chroma components).
  3. DCT:Performing Discrete Cosine Transform (DCT) on each of the MxN Luma and Chroma components.
  4. Scaling:Performing quantization of the resultant ouiput coefficient matrix given by DCT which of same size as input to this block.
  5. Scanning:Zig-Zag scaning of the resultant MxN matrix to a single dimensional array.
  6. Huffmancoding:Performing Huffman Coding on the resultant 1-D array.
  7. BitStream:And finally the resultant bitstream will be the JPEG encoder output.

In detail:

Reading 8x8 matrix of Red, Green and Blue components of input image. Converting each one of the RGB components to YCbCr (Luma and Chroam components) using below equation

Y = (0.299R + 0.587G + 0.114B) + 64
Cb = (-0.1687R - 0.3313G + 0.5B) + 512
Cr = (0.5R - 0.4187G - 0.0813B) + 512

And then performing 2D - DCT on each of the 8x8 matrix of Y, Cb and Cr

ref the link below.


DCT will give the lower frequency coefficients matrix 8x8 (Y,Cb and Cr).

which are more sensitive to human eye.

And then performing scalar quntization (scaling of resultant DCT output array) of each of the luma and chroma matrices.

This quantization is the major step in which the actual compression takes place and this is module which consumes more number of cycles in JPEG compression.

And performing zig-zag scanning on the resultant scaled arrays(Y, Cb and Cr).

Performing Huffman Run length coding on the resultant 1D array got after zig-zag coding.

The resultant array is the output bitstream of the JPEG encoder.


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