PPT-CS448f: Image Processing For Photography and Vision

Author : lois-ondreau | Published Date : 2016-04-26

Lecture 1 Today Introductions Course Format Course Flavor Lowlevel basic image processing Highlevel algorithms from Siggraph Introductions and Course Format httpcs448fstanfordedu

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CS448f: Image Processing For Photography and Vision: Transcript

Lecture 1 Today Introductions Course Format Course Flavor Lowlevel basic image processing Highlevel algorithms from Siggraph Introductions and Course Format httpcs448fstanfordedu Some Background Qs. Sharpening. Sharpening. Boost detail in an image without introducing noise or artifacts. Undo blur. due to lens aberrations. slight misfocus. Recall Denoising. Input. =. Signal. +. Noise. Blending and Pyramids. Blending. We’ve aligned our images. What now?. Averaging. Weighted averaging. min/max/median. Noise . reduction by Averaging. 2 Shots. 4 Shots. 8 Shots. 16 Shots. Noise Reduction by Averaging. http://www.santomarco.com/. http://michaelleadbetter.com.au/portfolio-Landscape-Photography-Brisbane.html. Landscape. http://phdavies.co.uk/2013/04/06/sylvia-plath-and-the-confessionals-of-90%E2%80%B2s-rock-pt-5/lana-del-rey-as-sylvia-plath-portrait/. Graph Cuts. Seam Carving. Video. Make images smaller by removing “seams”. Seam = connected path of pixels . from top to bottom. or left edge to right edge. Don’t want to remove important stuff. What is Fashion Photography?. The Genre:. Many other genres of photography come under the umbrella of ‘Fashion Photography’. Editorial Photography. Advertising Photography. Beauty Photography. What Do We Need to Think About?. 1. Image. Rich info. from visual data. Examples of images around us. natural photographic images; . . artistic and engineering drawings. scientific images (satellite, medical, etc.). “Motion pictures” => video. Tone Mapping. So far. So far. Tone Mapping. Some Images have too much dynamic range to display on a slide:. (belgium.hdr). Recall Sharpening. Input. =. Coarse . Fine. Tone Mapping. Input. Sharpening. Sharpening. Boost detail in an image without introducing noise or artifacts. Undo blur. due to lens aberrations. slight misfocus. Recall Denoising. Input. =. Signal. . Noise. Fast Filtering. Problems in Computer Vision. Computer Vision in One Slide. 1) Extract some features from some images . 2) Use these to formulate some . (hopefully linear) constraints. 3) Solve a . system of . Fast Filtering Continued. Filtering by . Resampling. This looks like we just zoomed a small image. Can we filter by . downsampling. then . upsampling. ?. Filtering by Resampling. Filtering by Resampling. . SYFTET. Göteborgs universitet ska skapa en modern, lättanvänd och . effektiv webbmiljö med fokus på användarnas förväntningar.. 1. ETT UNIVERSITET – EN GEMENSAM WEBB. Innehåll som är intressant för de prioriterade målgrupperna samlas på ett ställe till exempel:. Divya Spandana . Marneni. Agenda. What is Big Data. Big Data and image processing. Why to analyze big images. Complexity involved in processing. Hadoop Image processing framework. Image Retrieval in big data. Planning an Indian wedding photography involves meticulous attention to detail, from selecting the perfect venue to curating an exquisite menu. Amidst the flurry of preparations, choosing the right media coverage for your special day is paramount. While some opt to hire separate companies for Indian wedding photography and videography, there are numerous advantages to entrusting both aspects to a single service provider. Dr. Sonalika’s Eye Clinic provide the best Low vision aids treatment in Pune, Hadapsar, Amanora, Magarpatta, Mundhwa, Kharadi Rd, Viman Nagar, Wagholi, and Wadgaon Sheri

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