gsoc
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// September 13th, 2011 // c++ , code , google 4 months back, got a confirmation of my selection in Google Summer of Code 2011. It was a good feeling(Atleast I knew, that I won’t be vella this summer).
Google Summer of Code 2011 | | PRATIK ANAND |
Files: This page describes the basic RasterElement importer provided in the plug-in sampler. This is a basic importer which simulates loading from a file and provides a fixed 1 band data array.
Opticks: Creating a raster data importer plug-in
OpenMP and C++ Reap the Benefits of Multithreading without All the Work Kang Su Gatlin and Pete Isensee This article is based on a prerelease version of Visual C++ 2005. All information contained herein is subject to change.
OpenMP and C++: Reap the Benefits of Multithreading without All the Work
Presenter(s): Trevor Clarke, Opticks Kip Streithorst, Ball Aerospace & Technologies Corp. Opticks is an open source ELT designed for analysis of imagery, video, spectral, SAR, thermal, and other spatiotemporal data. Opticks was originally developed by Ball Aerospace & Technologies corp. for the US Air Force. In 2007, Ball and the USAF released the core ELT and a number of plug-ins as open source software.
Opticks: Releasing a government tool to the open source community | Free and Open Source Software for Geospatial
I love external libraries. A good library (one that is well-tested and interoperable) literally saves years of development time. Since this post revolves around C++, I'm going to mention Boost as one of the most helpful libraries ever made. Visual Studio provides a fairly obtuse (but working) system for referencing libraries on a per-user, per-system basis, accessable from the Tools > Options menu: It doesn't look the most user-friendly and it's a little bit painful to get to (especially the first time), but it got the job done. Theoretically, you only go into this menu (or you write a script to do it for you) once per library and never touch it again.
Travis Gockel: Visual Studio 2010: Property Sheets and C++ Directories
White Balance Correction by Using Photoshop « Just about Photography
White balance is IMPORTANT – but most of (newbie) photographers always use automatic white balance, a little bit ridiculous but that’s the fact. Honestly most of times I also use auto white balance although I know I can’t get the correct color/tone. Since I still use AWB but want to get the correct color then I need to correct the WB (in post processing) by using Photoshop.work - Understanding White Balance
White balance (WB) is the process of removing unrealistic color casts, so that objects which appear white in person are rendered white in your photo. Proper camera white balance has to take into account the "color temperature" of a light source, which refers to the relative warmth or coolness of white light. Our eyes are very good at judging what is white under different light sources, but digital cameras often have great difficulty with auto white balance (AWB) — and can create unsightly blue, orange, or even green color casts. Understanding digital white balance can help you avoid these color casts, thereby improving your photos under a wider range of lighting conditions.
Compiling and Building Plug-Ins
This document will describe how to compile your plug-ins once you have written code so that they can be loaded and executed inside Opticks. It is recommended that you first read Supported Compilers and Platforms if you haven't already to ensure you are using a supported platform and compiler. This document is broken into two sections. The first section, Compiling Basic Plug-Ins For Any Platform, Compiler, or Build Tool , describes the bare essentials needed to build plug-ins.This document will describe the options available to you when running your newly written plug-ins with Opticks. Two approaches to configuring Opticks to run your plug-ins will be presented. Following that is a more detailed section that describes all the necessary configuration for running Opticks. It is highly recommended that you read this entire document before deciding which approach is most appropriate for you. Approach 1: Use an Opticks installation This approach involves copying your plug-ins into an existing Opticks installation.
Running your plug-ins
noise reduction
UUID (GUID) Generator on the WEB
The following version 1 UUID / GUID is generated for your use: 82050000-992d-11e2-9e96-0800200c9a66 This UUID is generated according to RFC 4122 Using the timestap / nodeid version (version 1), where the nodeid comes from network equipment I own. This type of UUID is generated using the current time, a clock id which changes in case the current time is found to be older than the latest known time a UUID is generated and an IEE 802 hardware address which should be unique.Still the following disclaimer applies: Disclaimer: The provided UUID (GUID) is provided AS IS without warranty of any kind, not even the warranty that the generated UUID is actually unique. The entire risk of using this UUID is upto you. If you cannot agree to those terms do not use the generated UUID.
Common Names: Laplacian, Laplacian of Gaussian, LoG, Marr Filter Brief Description The Laplacian is a 2-D isotropic measure of the 2nd spatial derivative of an image. The Laplacian of an image highlights regions of rapid intensity change and is therefore often used for edge detection (see zero crossing edge detectors ). The Laplacian is often applied to an image that has first been smoothed with something approximating a Gaussian smoothing filter in order to reduce its sensitivity to noise, and hence the two variants will be described together here.
work - Spatial Filters - Laplacian/Laplacian of Gaussian
work - Decoding raw digital photos in Linux
Back to Dave Coffin's Home Page en Esperanto em Português auf Deutsch на русском па-беларуску Welcome!work - HowStuffWorks "Demosaicing Algorithms: Color Filtering"
A more economical and practical way to record the primary colors is to permanently place a filter called a color filter array over each individual photosite. By breaking up the sensor into a variety of red, blue and green pixels, it is possible to get enough information in the general vicinity of each sensor to make very accurate guesses about the true color at that location. This process of looking at the other pixels in the neighborhood of a sensor and making an educated guess is called interpolation .Convert Bayer pattern encoded image to truecolor image - MATLAB
Convert Bayer pattern encoded image to truecolor image Syntax RGB = demosaic(I, sensorAlignment)(This article has been translated to the Serbo-Croatian language by WHGeeks .) There's been some discussion recently about the color technology of CCD (charge-coupled device) sensors used in most digital cameras. In particular, the issue of the true resolution of the CCD versus the resolution of the image that it produces has arisen. To understand why these figures are different, you need to know a little about how the CCD in a camera works.