PPT-Digital Image Processing

Author : debby-jeon | Published Date : 2016-06-25

Lecture 3 Image Formation University Of Malakand Department of Computer Science UoMIPS Dr Engr Sami ur Rahman 2 Courtesy Brian Mac Namee Gonzalez and Woods

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Digital Image Processing: Transcript


Lecture 3 Image Formation University Of Malakand Department of Computer Science UoMIPS Dr Engr Sami ur Rahman 2 Courtesy Brian Mac Namee Gonzalez and Woods Contents This lecture will cover. Astrophotograpy. ….. My way. My camera. Why Canon?. Provides RAW files. Not directly useable as an image. “. Digital negatives”….unprocessed readout of pixels. Well suited for dark subtracting and flat fielding…. not true of Nikon. Overview. Images. Pixel Filters. Neighborhood Filters. Dithering. Image as a Function. We can think of an . image . as a function, . f. , . f:. . R. 2. . . . R. f . (. x, y. ). . gives the . intensity. Achieving balance of compliance with customer experience and opportunity. 30 September 2015. Paula Barrett. Partner. Data protection . c. ompliance . Personal data – can you spot it?. “Personal Data” means data which relate to a living individual who can be identified:. Processing Computations with . Molecular Reactions. Hua. Jiang. PhD Candidate, Electrical Engineering . University . of . Minnesota. . Advisors. Professor . Keshab. . Parhi. and Professor Marc Riedel. Pumice Depth Below . Water . as a Function of Time. Behnaz. Hosseini. Havre, MESH . and Pumice Experiments. P. umice deposits from 2012 . Kermadec. Islands submarine eruption north of New Zealand. Havre caldera samples collected by MESH team using remotely operated vehicle Jason. r. s. t. u. v. w. x. y. z. Origin. x. y. Image f (x, y). e. processed. = . v. *e + . . r. *a + . s. *b + . t. *c + . . u. *d + . w. *f + . . x. *g + . y. *h + . z. *. i. Filter. Simple 3*3. Neighbourhood. Hel-Or . . toky@idc.ac.il . Image Processing. Spring 2010. 2. Administration. Pre-requisites / prior knowledge. Course Home Page:. http://. www1.idc.ac.il/toky/ImageProc-10. “What’s new” . Lecture slides and handouts . Overview. What’s in the toolboxes. Learn basic techniques to use them. Using MATLAB’s built in help and demos. Setup. Log in to your machines. Start MATLAB. Open a web browser and type in:. http://tinyurl.com/uta-tut. 22 . June . 2016. Digital Artwork. Screen Capture of Desktop. Digital Photograph (Portrait). Digital Photograph (Landscape). Digital Photograph (Still Life). Digital Photo Editing (B&W). Original Image. Madan Musuvathi. . Visiting Professor, UCLA . Principal Researcher, Microsoft Research. Mid-point feedback. Are you learning from the papers we are reading?. Do you find class discussions helpful?. Does preparing for the class presentation help? . The relevant features for the examination task are enhanced. The irrelevant features for the examination task are removed/reduced. Here the input and output image are both digital image in color or gray scale.. Recognition Vol.7, No. 2 (2014), pp. 3 89 - 3 9 8 http://dx.d oi.org/10.14257/ijsip.2014.7. 2 . 3 6 ISSN: 2005 - 4254 IJSIP Copyright ⓒ 201 4 SERSC Extraction of Optic Cup in Retinal Fundus image adjusts its coefficients . to adapt input signal . via an adaptive algorithm. .. Applications:. Signal enhancement. Active noise control. Noise cancellation. Telephone echo cancellation. 1. Text: Digital Signal Processing by Li Tan, Chapter 10. KK. -. Komputasi. . dan. . Kecerdasan. . Buatan. Teknik. . Komputer. Universitas. . Komputer. Indonesia-UNIKOM. John Adler. Wednesday, September 19, 2012. 1. TK 37404 . Pengolahan. Citra. Bahan.

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