What is Body Imaging Enhancement?

Image enhancement, also known as image enhancement, is a process of improving the visual quality of an image or highlighting certain features by adjusting and changing the density or hue of the image. The purpose is to improve image interpretation performance and effect.

The content is very wide, mainly including zoom, stereo effect, color enhancement, contrast enhancement (contrast expansion), edge enhancement (image sharpening), image smoothing and sharpening, image calculation (ratio image), etc. There are many methods, such as algebraic operations, contrast transformation, filtering, and color processing, etc., which can be implemented through a series of technologies and equipment. There are two general types of equipment, namely optical-electronic equipment and digital image processing equipment. The former is simple, convenient, low cost, and easy to popularize, but the processing accuracy is relatively low; the latter is flexible, fast, good reproducibility, high precision, but the equipment is expensive. Optical-electronic image enhancement mainly includes color synthesis, density segmentation, and related masks.

With the reference of foreign mature theoretical systems and technology application systems, domestic enhanced technologies and applications have also developed greatly. In general, the development of image enhancement technology has roughly gone through four stages: the start-up period, the development period, the popularization period, and the application period.

The start-up period began in the 1960s. At that time, the images were scanned and displayed using pixel-type rasters, and most of them were processed by mainframes. In this period, due to the high cost of image storage and the high cost of processing equipment, its application area was very narrow.

The 1970s entered a period of development. A large number of medium and large-scale computers were used for processing. Image processing was gradually changed to raster scanning display methods. In particular, CT and satellite remote sensing images appeared, which proposed a higher level of image enhancement processing. Claim.

In the 1980s, image enhancement technology entered a period of popularity, at which time computers were able to assume the task of graphics and image processing.

The 1990s entered the application period, and people used digital image enhancement technology to process and analyze remote sensing images to effectively conduct resource and mineral exploration, surveys, agricultural and urban land planning, crop estimation, weather forecasting, disasters, and military objectives. Monitoring, etc.

In biomedical engineering, the use of image enhancement technology

There are many factors that affect the clarity of image quality. Outdoors

In more than 40 years, image processing has rapidly developed into an independent and vigorous subject. Image enhancement technology has gradually covered all aspects of human life and social production. Below we only give some examples of applications in several aspects.

Image enhancement aerospace

As early as the early 1960s, the successful development of 3rd generation computers and the development of fast Fourier transforms enabled image enhancement technology to be implemented on computers.

1964 Researchers at the US Jet Propulsion Laboratory (JPL) used IBM7094 computers and other equipment to apply set correction, grayscale transform, noise reduction, Fourier transform, and two-dimensional linear filtering to the spacecraft "Wanderer 7 The thousands of photos of the moon sent back were successfully processed. Subsequently, they performed more complex digital image processing on the tens of thousands of photos of "Wanderer 8" and "Sailor" back to Earth, which further improved the image quality. Since then, image enhancement technology has entered the aerospace field. Research and Application.

At the same time, the development of image enhancement technology has also promoted the improvement of hardware equipment. For example, the resolution of LANDSAT-4 in 1983 was 30m, and the resolution of satellites launched today can reach 3-5m. Improving the performance of image acquisition equipment has greatly improved the quality of captured images and the accuracy and clarity of the data. ^[2]

Image enhancement biomedical field

There are two types of image enhancement technologies in biomedical applications. One is the processing and analysis of biomedical micro-optical images, such as the classification and counting of red blood cells, white blood cells, bacteria, eggs, and chromosomes; the other is A similar application is the processing of X-ray images, the most successful of which is computed tomography. In 1973, the British EMI company manufactured the first X-ray tomography device. Some tissues of the human body, such as the soft tissues of the heart and breast, have little change in attenuation of X-rays, resulting in weak image sensitivity. As a result, image enhancement technology has been widely used in biomedical imaging. ^[2]

Image enhancement industrial production

Image enhancement is widely used in industrial production automation design and product quality inspection, such as inspection and identification of mechanical parts, inspection of printed circuit boards, quality inspection before food packaging, inspection of workpiece dimensions, inspection of integrated chip internal circuits and many more. In addition, computer vision can also be applied to industrial production. The pictures taken by the camera are sent to the robot through enhanced processing, data encoding, and compression. Through a series of controls and transformations, the position, direction, attributes, and other states of the target can be determined. Realize robots complete special tasks according to human will. ^[2]

Imaging Public Safety

In terms of social security management, the application of image enhancement technology is also very extensive, such as non-destructive security inspection, fingerprint, iris, palm print, face enhancement and other biological features. Image enhancement processing is also applied to traffic monitoring, and target locations are locked by TV tracking technology, such as analysis of foggy images, night vision infrared images, and traffic accidents. ^[2]