Search Results for "image processing c source code"
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Showing 4 open source projects for "image processing c source code"
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IM is a toolkit for Digital Imaging. IM is based on 4 concepts: Image Representation, Storage, Processing and Capture. The main goal of the library is to provide a simple API and abstraction of images for scientific applications.
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LCUI
A small C library for building user interfaces with C, XML and CSS
Build simple desktop apps with C, XML and CSS. LCUI is a simple GUI library, it is written in C, supports XML and CSS, you can use C, XML and CSS to build simple desktop applications, at present it is mainly supported by Windows, subsequent versions will improve support for Linux. If you have web development experience, then the use of LCUI will be easier to get started, because LCUI's XML, CSS, and element layout processing effects are similar to web browser, you can refer to the sample... -
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IBEX_MDA
An open infrastructure software to facilitate radiomics research.
This web page is not guaranteed to have the latest versions. The latest stand-alone version can be downloaded at http://bit.ly/IBEX_MDAnderson The latest source-code version can be downloaded at http://bit.ly/IBEXSrc_MDAnderson IBEX (imaging biomarker explorer) is an open infrastructure software platform that flexibly supports common radiomics workflow tasks such as multimodality image data import and review, development of feature extraction algorithms, model validation, and consistent data sharing among multiple institutions. ... -
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HIPAcc
Heterogeneous Image Processing Acceleration (HIPACC) Framework
HIPAcc development has moved to github: https://github.com/hipacc HIPAcc allows to design image processing kernels and algorithms in a domain-specific language (DSL). From this high-level description, low-level target code for GPU accelerators is generated using source-to-source translation. As back ends, the framework supports CUDA, OpenCL, and Renderscript. HIPAcc allows programmers to develop imaging applications while providing high productivity, flexibility and portability as well as competitive performance: the same algorithm description serves as basis for targeting different GPU accelerators and low-level languages. -
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