Engineering
Engineering
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Nasir Ahmed
Nasir Ahmed
Born 1940; 84 years ago (1940)
Bangalore, Kingdom of Mysore, British India
Nationality
Education
  • Bishop Cotton Boys' School
  • University Visvesvaraya College of Engineering (BSc),
  • University of New Mexico (MSc, PhD)
Known for
Spouse(s) Esther Parente-Ahmed
Children Michael Ahmed Parente
Awards
  • 1982  Distinguished Graduate Faculty Member Award Kansas State University
  • 1985  IEEE Fellow
  • 2001  Distinguished Engineering Alumnus Award University of New Mexico
Scientific career
Fields
Thesis
Doctoral advisor Shlomo Karni

Nasir Ahmed (born 1940) is an Indian-American electrical engineer, computer scientist and mathematician. He is Professor Emeritus of Electrical and Computer Engineering at University of New Mexico (UNM). He is best known for inventing the discrete cosine transform (DCT) in the early 1970s. The DCT is the most widely used data compression transformation, the basis for most digital media standards (image, video and audio) and commonly used in digital signal processing. He also described the discrete sine transform (DST), which is related to the DCT.[1]

Nasir Ahmed was a pioneer of digital media. His DCT algorithm "played a major role in allowing digital files to be transmitted across computer networks."[2]

Personal life[]

Nasir Ahmed was born in Bangalore, India, in 1940. He was raised by his maternal grandparents. His grandfather was an electrical engineer who had previously worked for General Electric in the United States in 1919. He inspired Nasir to pursue an electrical engineering career in the United States. In 1961, he earned a bachelor's degree in electrical engineering at Bangalore's University of Visvesvaraya College of Engineering, In the fall of that year, he enrolled for graduate school at the University of New Mexico in Albuquerque, United States. Ahmed earned a master’s degree in electrical engineering by 1963 and then a PhD in 1966.[2]

During his first year in Albuquerque, he met Esther Parente, a student from Argentina. They married while he was working on his doctorate. They have remained married for 60 years, as of 2024.[2]

Discrete cosine transform (DCT)[]

After Ahmed completed his PhD in 1966, he was hired as a principal research engineer at Honeywell’s new computer division. He learnt about Walsh functions, a technique for analyzing digital representations of analog signals, which he realized had many potential applications. Ahmed focused on using signal-processing and analysis techniques to efficiently reduce the file size of a digital image without losing significant visual detail. He continued his research on data compression when he was hired as a professor in electrical and computer engineering at Kansas State University in 1968.[2]

The discrete cosine transform (DCT) is a lossy compression algorithm that was first conceived by Ahmed while working at the Kansas State University, and he proposed the technique to the National Science Foundation in 1972. He originally intended the DCT for image compression.[3][4] However, his proposal was rejected because "the reviewers said the idea was too simple, so they rejected the proposal.[2]

Ahmed then developed a working DCT algorithm with his PhD student T. Natarajan and friend K. R. Rao in 1973, and they found that it was the most efficient algorithm for image compression.[3] They tested the algorithm with images that they compressed down to one-tenth the original size while looking sufficiently similar to the original images.[2] They presented the results in their seminal January 1974 paper.[5][6][7] It described what is now called the type-II DCT (DCT-II),[8]: 51  as well as its inverse, the type-III DCT (a.k.a. IDCT).[5]

Ahmed was the leading author of the benchmark publication,[9][10] Discrete Cosine Transform (with T. Natarajan and K. R. Rao),[5] which has been cited as a fundamental development in thousands of works since its publication.[11] The basic research work and events that led to the development of the DCT were summarized in a later publication by Ahmed entitled "How I came up with the Discrete Cosine Transform" in 1991.[3]

The DCT is widely used for digital image compression.[12][13][14] It is a core component of the 1992 JPEG image compression technology developed by the JPEG Experts Group[15] working group and standardized jointly by the ITU,[16] ISO and IEC. A tutorial discussion of how it is used to achieve digital video compression in various international standards defined by ITU and MPEG (Moving Picture Experts Group) is available in a paper by K. R. Rao and J. J. Hwang[17]: JPEG: Chapter 8; H.261: Chapter 9; MPEG-1: Chapter 10; MPEG-2: Chapter 11  which was published in 1996, and an overview was presented in two 2006 publications by Yao Wang.[18][19] The image and video compression properties of the DCT resulted in its being an integral component of the following widely used international standard technologies:

Standard Technologies
JPEG Storage and transmission of photographic images on the World Wide Web (JPEG/JFIF); and widely used in digital cameras and other photographic image capture devices (JPEG/Exif).
MPEG-1 Video Video distribution on CD or via the World Wide Web.
MPEG-2 Video (or H.262) Storage and handling of digital images in broadcast applications: digital TV, HDTV, cable, satellite, high speed internet; video distribution on DVD.
H.261 First of a family of video coding standards (1988). Used primarily in older video conferencing and video telephone products.
H.263 Videotelephony and videoconferencing

The form of DCT used in signal compression applications is sometimes referred to as DCT-2 in the context of a family of discrete cosine transforms,[20] or as DCT-II.

More recent standards have used integer-based transforms that have similar properties to the DCT but are explicitly based on integer processing rather than being defined by trigonometric functions.[21] As a result of these transforms having similar symmetry properties to the DCT and being, to some degree, approximations of the DCT, they have sometimes been called "integer DCT" transforms. Such transforms are used for video compression in the following technologies pertaining to more recent standards. The "integer DCT" designs are conceptually similar to the conventional DCT but are simplified to provide exactly specified decoding with reduced computational complexity.

Standard Technologies
VC-1 Windows media video 9, SMPTE 421.
H.264/MPEG-4 AVC The most commonly used format for recording, compression and distribution of high definition video; streaming internet video; Blu-ray Discs; HDTV broadcasts (terrestrial, cable and satellite).
H.265/HEVC Successor to the H.264/MPEG-4 AVC standard having substantially improved compression capability.
H.266/VVC Successor to HEVC having substantially improved compression capability.
WebP Images A graphic format that supports the lossy compression of digital images. Developed by Google.
WebM Video A multimedia open source format intended to be used with HTML5. Developed by Google.

A DCT variant, the modified discrete cosine transform (MDCT), is used in modern audio compression formats such as MP3,[22] Advanced Audio Coding (AAC), and Vorbis (OGG).

The discrete sine transform (DST) is derived from the DCT, by replacing the Neumann condition at x=0 with a Dirichlet condition.[8]: 35 The DST was described in the 1974 paper by Ahmed, Natarajan and Rao.[5]

Ahmed later was involved in the development a DCT lossless compression algorithm with Giridhar Mandyam and Neeraj Magotra at the University of New Mexico in 1995. This allows the DCT technique to be used for lossless compression of images. It is a modification of the original DCT algorithm, and incorporates elements of inverse DCT and delta modulation. It is a more effective lossless compression algorithm than entropy coding.[23]

Background[]

  • Alumnus of the Bishop Cotton Boys' School; received his B.S. degree in Electrical Engineering from the University Visvesvaraya College of Engineering, Bangalore in 1961;
  • Received his M.S. and Ph.D. degrees in Electrical and Computer Engineering from the University of New Mexico in 1963 and 1966, respectively. His doctoral dissertation adviser was Shlomo Karni;
  • Principal Research Engineer, Honeywell, St. Paul, Minnesota from 1966–68;
  • Professor, Electrical and Computer Engineering Department, Kansas State University, 1968–83;
  • 1983-2001: University of New Mexico—Presidential Professor of Electrical and Computer Engineering, 1983–89; Chair, Department of Electrical and Computer Engineering, 1989–94; Dean of Engineering, 1994–96; Associate Provost for Research and Dean of Graduate Studies, 1996–2001;
  • Consultant, Sandia National Laboratories, Albuquerque, New Mexico, 1976–90.
  • Married to Esther Parente-Ahmed. Son, Michael Ahmed Parente.

Books[]

Popular culture[]

In season 5, episode 8 of NBC's This Is Us, Ahmed's story was told to highlight the importance of image and video transmission over the Internet in modern society, particularly during the COVID-19 pandemic. The episode ends with a picture of Ahmed and his wife, along with captions explaining the importance of his work, and that producers spoke to the couple over video chat to understand their story and incorporate it into the episode.[24] Nasir Ahmed is portrayed by actor Abhi Sinha, while his wife Esthar is portrayed by actress Katie Sarife.[25]

References[]

  1. "Who is Nasir Ahmed? Real love story of Indian-American engineer on 'This Is Us' who is credited for .jpg algorithm". meaww.com. Retrieved 2022-04-08.
  2. 2.0 2.1 2.2 2.3 2.4 2.5 Jones, Willie D. (19 August 2024). "Nasir Ahmed: An Unsung Hero of Digital Media". IEEE Spectrum. Retrieved 2024-08-25.
  3. 3.0 3.1 3.2 Ahmed, Nasir (January 1991). "How I Came Up With the Discrete Cosine Transform". Digital Signal Processing. 1 (1): 4–5. doi:10.1016/1051-2004(91)90086-Z.
  4. Stanković, Radomir S.; Astola, Jaakko T. (2012). "Reminiscences of the Early Work in DCT: Interview with K.R. Rao" (PDF). Reprints from the Early Days of Information Sciences. Tampere International Center for Signal Processing. 60. ISBN 978-9521528187. ISSN 1456-2774. Archived (PDF) from the original on 30 December 2021. Retrieved 30 December 2021 – via ETHW.
  5. 5.0 5.1 5.2 5.3 —; Natarajan, T. Raj; Rao, K.R. (1 January 1974). "Discrete Cosine Transform". IEEE Transactions on Computers. IEEE Computer Society. C-23 (1): 90–93. doi:10.1109/T-C.1974.223784. eISSN 1557-9956. ISSN 0018-9340. LCCN 75642478. OCLC 1799331. S2CID 39023640.
  6. Rao, K. Ramamohan; Yip, Patrick C. (11 September 1990). Discrete Cosine Transform: Algorithms, Advantages, Applications. Signal, Image and Speech Processing. Academic Press. arXiv:1109.0337. doi:10.1016/c2009-0-22279-3. ISBN 978-0125802031. LCCN 89029800. OCLC 1008648293. OL 2207570M. S2CID 12270940.
  7. "T.81 – Digital compression and coding of continuous-tone still images – requirements and guidelines" (PDF). CCITT. September 1992. Retrieved 12 July 2019.
  8. 8.0 8.1 Britanak, Vladimir; Yip, Patrick C.; Rao, K. R. (6 November 2006). Discrete Cosine and Sine Transforms: General Properties, Fast Algorithms and Integer Approximations. Academic Press. ISBN 978-0123736246. LCCN 2006931102. OCLC 220853454. OL 18495589M. S2CID 118873224.
  9. Selected Papers on Visual Communication: Technology and Applications, (SPIE Press Book), Editors T. Russell Hsing and Andrew G. Tescher, April 1990, pp. 145-149 [1].
  10. Selected Papers and Tutorial in Digital Image Processing and Analysis, Volume 1, Digital Image Processing and Analysis, (IEEE Computer Society Press), Editors R. Chellappa and A. A. Sawchuk, June 1985, p. 47.
  11. Nasir Ahmed publications indexed by Google Scholar
  12. Andrew B. Watson (1994). "Image Compression Using the Discrete Cosine Transform" (PDF). Mathematica Journal. 4 (1): 81–88.
  13. image compression.
  14. Transform coding.
  15. Wallace, G. K. (February 1992). "The JPEG Still Image Compression Standard" (PDF). IEEE Transactions on Consumer Electronics. 38 (1). doi:10.1109/30.125072..
  16. CCITT 1992 [2].
  17. Rao, K. R.; Hwang, J. J. (18 July 1996). Techniques and Standards for Image, Video, and Audio Coding. Prentice Hall. ISBN 978-0133099072. LCCN 96015550. OCLC 34617596. OL 978319M. S2CID 56983045.
  18. Yao Wang, Video Coding Standards: Part I, 2006
  19. Yao Wang, Video Coding Standards: Part II, 2006
  20. Gilbert Strang (1999). "The Discrete Cosine Transform" (PDF). SIAM Review. 41 (1): 135–147. Bibcode:1999SIAMR..41..135S. doi:10.1137/S0036144598336745.
  21. Lee, Jae-Beom; Kalva, Hari (2008). The VC-1 and H.264 Video Compression Standards for Broadband Video Services. Springer Science+Business Media, LLC. pp. 217–245.
  22. Guckert, John (Spring 2012). "The Use of FFT and MDCT in MP3 Audio Compression" (PDF). University of Utah. Retrieved 14 July 2019.
  23. Mandyam, Giridhar D.; Ahmed, Nasir; Magotra, Neeraj (17 April 1995). Rodriguez, Arturo A.; Safranek, Robert J.; Delp, Edward J. (eds.). "DCT-based scheme for lossless image compression". Digital Video Compression: Algorithms and Technologies 1995. SPIE. 2419: 474–478. Bibcode:1995SPIE.2419..474M. doi:10.1117/12.206386. S2CID 13894279.
  24. Mizoguchi, Karen (February 16, 2021). "How This Is Us Honored the Real-Life 'Genius' Who Made It Possible for the Pearsons to Stay Connected amid COVID". People.com. Retrieved 21 March 2022.
  25. https://www.imdb.com/title/tt13841384/fullcredits

External links[]

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