Digital Imaging

Digital imaging Digital imaging inevitably impairs the status of a photograph as essentially a true medium. Discuss. Until recently, at least photography was able to be defined as a process involving optical, photosensitive materials, and chemical processing of materials for producing prints or slides. But today, this definition may change. Technological innovation ... Transfer photos from the original chemical foundation to electronics ... We already know that the emergence of this new technology is changing the essence of photography, it is not an exaggeration.

First, it was important to explain the difference between digital image processing and digital image analysis. Image processing can be thought of as transforming an image into an image, ie a transformation in which a modified (highlighted) image is obtained from the beginning of the image. Digital image analysis, on the other hand, converts the image to something different from that image. In other words, it generates information that describes explanations and decisions. Digital image processing has three objectives; to improve the look of the image to the human observer, to extract quantitative information invisible to the eyes from the image, and to extract the image with luminance or geometric terms To calibrate. Image processing is both art and science. This is an interdisciplinary field that includes elements of photography, computer technology, optics, electronics, mathematics.

The earliest application of image processing to digital images dates back to the 1920's when telegraphy was needed to improve the quality of images transmitted over long distances. In the 1960's, image processing became to analyze and manipulate digital images, especially to improve its quality, when digital computers became powerful enough to execute important data. After the invention of computed tomography (CAT) by Sir Godfrey N. Hounsfield and Professor Allan M. Cormack (also known as computed tomography (CT)), the application of digital image processing began with biomedical science . Since the 1980's, the application of digital image processing technology began in various fields such as image enhancement / recovery, artistic effect, medical visualization, industrial inspection, law enforcement agency, human machine interface.

Image analysis is a morphometric technique for acquiring information from digital images using processing tools that segment pixels in digital images based on color or density (Figures 4.5A and B). The segmented image is then used to quantify the area of ​​a particular feature (defined by the pixel), such as the region that is positively stained by the IHC. When integrated with slide digital imaging as a whole, image analysis can be an efficient and effective tool because it can automate most of the processes necessary to obtain objective unbiased data. Image analysis is not as accurate as stereochemistry, it only provides a measure of the relative change of interest (Table 4.3). Image analysis can be used to measure the relative area of ​​positive immunostaining of proteins, cells or structures in tissues (FIGS. 4.5C and D). In addition, when comparing objects of different sizes and calculating outlines of the cells, large objects are counted more frequently than small objects.