IT 472 Digital Image Processing Asim Banerjee Faculty

IT 472 Digital Image Processing Asim Banerjee Faculty Block #1, Room No. 1109 Extn. # 554 IT 472 - Digital Image Processing

Psychovisual Redundancy (1/2) • The brightness of a region as perceived by the eye, depends on factors other than simply the light reflected by the region. NOTE: Mach bands can be perceived in an area of constant intensity. • Such a phenomena result from the fact that the eye does not respond with equal sensitivity to all visual information i. e. certain information has less relative importance than other information in normal visual processing. IT 472 - Digital Image Processing 2

Psychovisual Redundancy (2/2) • This relatively less important information is said to be psychovisually redundant and can be easily eliminated without significantly impairing the quality of the perceived image. • Psychovisual redundancy is associated with real or quantifiable visual information. NOTE: Since elimination of psychovisually redundant data results in a loss of quantitative information, it commonly referred to as quantization. IT 472 - Digital Image Processing 3

Fidelity Criteria • Removal of psychovisually redundant information results in a loss of real or quantifiable visual information. • Because information of interest may be lost, a repeatable or reproducible means of quantifying the nature and extent of information loss is highly desirable. • Two general classes of criteria are used as a basis for assessment – Objective fidelity criteria – Subjective fidelity criteria IT 472 - Digital Image Processing 4

Objective Fidelity Criteria • When the level information loss is expressed as a function of the original or input image and the compressed and subsequently decompressed image, it is said to be based on an objective fidelity criteria. • Example – Root mean square error (RMSE) between the input and the output images. – Mean square signal to noise ratio of the compressed-decompressed image. IT 472 - Digital Image Processing 5

Subjective Fidelity Criteria • Although objective fidelity criteria offer a simple and convenient mechanism for evaluating information loss, most decompressed image are ultimately viewed humans, hence subjective evaluation by human observer is often more appropriate • The typical mechanism is to have observers rate the images on a scale of (say) – 4 to represent their subjective evaluation. NOTE: -4 worst 0 the same 4 best IT 472 - Digital Image Processing 6

Image Compression Models • Source encoder and decoder – Reduces or eliminates any coding, interpixel and/or psycho visual redundancies in the input image. • Channel encoder and decoder – Plays an important role when the channel is noisy or prone to error by inserting “controlled redundancy”. IT 472 - Digital Image Processing 7

Types of Compression • Lossless compression – Huffman coding – Bit-plane coding – Run length coding • Lossy compression – Lossy predictive coding – Transform coding – JPEG IT 472 - Digital Image Processing 8

Huffman Coding (1/2) • It is the most popular technique for removing coding redundancy. • When coding the symbols of an independent source individually, it yields the smallest possible number of code symbols per source symbol. • It involves a series of source reductions by ordering the probabilities of symbols under consideration and combining the two lowest probability symbols into a single symbol that replaces them in the next source reduction. IT 523 - Digital Image Processing 9

Source Reductions - Example Source: “Digital Image Processing” by R. C. Gonzalez and R. E. Woods • A series of source reductions by ordering the probabilities of symbols under consideration and combining the bottom two lowest probability symbols into a single symbol that replaces them in the next source reduction. IT 523 - Digital Image Processing 10

Huffman Coding (2/2) • The second step is to code each reduced source starting with the smallest source and working backwards to the original source. Source: “Digital Image Processing” by R. C. Gonzalez and R. E. Woods • The Huffman code is an instantaneous uniquely decodable block code. IT 523 - Digital Image Processing 11

Bitplane Coding (1/2) • It reduces the images interpixel redundancies by processing the image’s bit planes individually. • The multilevel images are decomposed into a series of binary images and then compressing the binary images using one of the several wellknown binary compression methods. • The images are often first gray coded before the bit plane decomposition is carried out to avoid too many 0 to 1 transitions across bit planes for pixel values that are close to each other. IT 523 - Digital Image Processing 12

Bitplane Coding Normal (2/2) Gray coded Normal Gray coded Source: “Digital Image Processing” by R. C. Gonzalez and R. E. Woods IT 523 - Digital Image Processing 13

Run-length Coding (1/2) 1 -D run length coding • Represents each row or column of an image or a bit plane by a sequence of lengths that describe successive runs of black and white pixels. • It is a standard compression approach in facsimile (FAX) coding. • It involves specifying the value of the gray level and the length of that run. IT 523 - Digital Image Processing 14

Run-length Coding (2/2) • The most common approaches determining the value of a run are for – Specify the value of the first run of each row – To assume that each row begins with a white run whose run length may be zero. NOTE: One can employ variable length coding on the run lengths themselves to achieve further compression. • The same can be extended to 2 -D run length coding. IT 523 - Digital Image Processing 15

Assignment • What is LZW coding? • Give an example of using LZW coding. • What are the tradeoffs involved in LZW coding? Submit by: 12: 00 hrs on 6 th March 2011. IT 472 - Digital Image Processing 16

Transform Coding System Source: “Digital Image Processing” by R. C. Gonzalez and R. E. Woods IT 523 - Digital Image Processing 17

Compression Standards • Jointly developed and sanctioned by – International Standardization Organization (ISO) – Consultative Committee of the International Telephone and Telegraph (CCITT) • Examples – JPEG standard – MPEG standard (MPEG 1 and MPEG 2) IT 472 - Digital Image Processing 18

Assignment • Write a short report on – JPEG standard (JPEG and JPEG 2000) – MPEG standards (viz. MPEG 1, MPEG 2, MPEG 4, MPEG 7 and MPEG 21) Submit by: 12: 00 hrs on 6 th March 2011. IT 472 - Digital Image Processing 19

That’s all for now. We shall continue in the next class. IT 472 - Digital Image Processing 20