Image processing is the process of running a digital image through an algorithm. This allows the raw input and overcomes every obstacle like noise and disturbances. These raw images are used to enhance the algorithm and extract the information from it and finding patterns.
Some of the best image processing software are:
1. OpenCV: It is one of the most used and popular image processing programming libraries and initially developed by the research unit of Intel in 1999. It is written in C++ but also comes with Python wrapper. Moreover, it works with almost all the major libraries of python and makes it easier for anyone to do research using real-time video. It is also compatible with all languages so making a bridge between them would be comparably easy.
It can be used for :
Advance vision research.
Disseminate vision knowledge.
Advance vision-based commercial applications.
2. MATLAB: Matlab is a multi-paradigm numerical computing environment and programming language developed by MathWorks. It provides a comprehensive set of reference-standard algorithms and workflow apps for image processing, analysis, visualization, and algorithm development. It works with C/C++ for fast deployment. Though it is paid and not that cheap and also not very easy to get.
It can be used for :
Image segmentation.
Image enhancement.
Noise reduction.
Geometric transformations.
Image registration.
3D image processing.
3. NVIDIA CUDA: NVIDIA has a big name in graphics and design and it has created an image processing software that can be used for fast development. It is a parallel computing platform and programming model developed by NVIDIA, developers are able to dramatically speed up computing applications by harnessing the power of GPUs. It works with most popular languages such as C, C++, Fortran, Python, and MATLAB and expresses parallelism through extensions in the form of a few basic keywords.
It can be used for:
Push-relabel maximum flow algorithm.
Fast sort algorithms of large lists.
Two-dimensional fast wavelet transform.
Molecular dynamics simulations.
Machine learning.
4. Scilab Image Processing Toolbox: It's a toolbox made by Scilab written in C and Scilab. It is meant to be a free, complete, and useful image toolbox for Scilab. Its goals include tasks such as filtering, blurring, edge detection, thresholding, histogram manipulation, segmentation, mathematical morphology, and color image processing. Scilab itself consists of different image processing library in it but has a different syntax which needed to be learned. It is majorly made using ImageMagick.
5. Amira: Amira is a software platform for 3D and 4D data visualization, processing, and analysis. It is being actively developed by Thermo Fisher Scientific in collaboration with the Zuse Institute Berlin. It is a bioimage processing software that helps in identifying the problem in the human body and also it helps marine biologists a lot. It is majorly used by thousands of researchers. This allows the user to mark (or segment) structures and regions of interest in 3D image volumes using automatic, semi-automatic, and manual tools. It can be also deployed using C++.
It can be used for :
Specific readers for microscopy data.
Image deconvolution.
Exploration of 3D imagery obtained from virtually any microscope.
Extraction and editing of filament networks from microscopy images.
Import of clinical and preclinical data in DICOM format.
Generation of 3D finite element (FE) meshes from segmented image data.
Support for many state-of-the-art FE solver formats.
High-quality visualization of simulation mesh-based results, using scalar, vector, and tensor field display modules.
Reconstruction and analysis of neural and vascular networks.
Visualization of skeletonized networks.
Skeletonization of quite large images.
There are many more image processing software depending on the use also since there are many available to different fields. ImageJ, ANIMAL, GNU Octave these are also suitable options available and can be considered. there are python libraries like Pillow, Matplotib, and other also available, and image processing is made easy now and can be done easily.
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Learn Electronics India's blog on image processing software is an invaluable resource. The top 5 recommendations have been carefully chosen, and the explanations are spot-on. This article has saved me a lot of time and effort in my search for the perfect software.
LearnElectronics India simplifies complex concepts beautifully. Thank you!