When developing hybrid mobile solutions one of the major challenges every developer faces is to handle the device fragmentation. There are an overwhelming number of devices out there, that it is sometimes impossible to cater to all of them and to provide a uniform user experience through a single hybrid mobile solution. Continue reading
Almost all images and photographs we come across are colored images. But for simplicity of algorithms most image processing algorithms are based on gray images (single channel). Even though colors play an important role in giving humans a true feel for images when it comes to details gray images and color images preserve the same amount of luminance and variation terms of details. Therefore even though the color information is lost, by converting an image to grayscale the details are still preserved.
Image processing is one of those areas I find a lot of interest. Editing, making enhancements to photos and merging multiple images into a single image can be one of the most creative past times for designers. However developers too could play around with pixels as designers do, and this in fact is known as image processing. It deals with manipulating pixels in an image using code.
Image processing branches out into many research areas such as medical, astronomy, chemistry. Mostly enhancing images for better clarity, extracting out hidden details in an image, enhancing segments of an image are typical uses of Image processing.
This post deals with using HTML5 in the context of image processing. With the improvement of modern browsers now it is possible to perform complex image processing algorithms simply with the context of a web browser.
When it comes to Image processing grayscale images are used to reduce the complexity of processing 3 separate R,G,B channels. Since gray images preserve the same luminosity of the color images, gray image processing algorithms can easily be ported to color images.