Digital image processing Digital image processing deals with manipulation of digital images through a digital computer. It is a subfield of signals and systems but focus particularly on images. DIP focuses on developing a computer system that is able to perform processing on an image. The input of that system is a digital image and the system process that image using efficient algorithms, and gives an image as an output. The most common example is Adobe Photoshop. It is one of the widely used application for processing digital images.

Digital image processing cont. Image processing is a method to perform some operations on an image, in order to get an enhanced image or to extract some useful information from it. It is a type of signal processing in which input is an image and output may be image or characteristics/features associated with that image. Nowadays, image processing is among rapidly growing technologies. It forms core research area within engineering and computer science disciplines too.

The origins of Digital image processing Computer Advances Computer Advances ƒ  the invention of the transistor by Bell Labs. in 1948 ƒ  the development of the high-level programming languages ƒ  the invention of the IC at Texas Instruments in 1958 ƒ  the development of operation systems in the early 1960s  the development of microprocessor by Intel in the early  1970s ƒ introduction by IBM of the personal computer in 1981 ƒ  Large Scale IC in the late 1970s ƒ  VLSI in the 1980s, ULSI present ƒ  IC Technology, Mass storage and display systems ƒ  Computers have powerful processing capability to process images.

ƒ Image processing applications Image processing applications ƒ From 1960s to present ƒ  image processing are used in a broad range of applications ƒ  Contract enhancement or code the intensity into color ƒ]  X-RAY, Industrial, Medicine, Biological sciences ƒ  to study pollution patterns from aerial and satellite imagery ƒ  Image enhancement and restoration ƒ  used to process degraded images of unrecoverable objects or experimental results too expensive to duplicate ƒ Archeology( 考 古學 ) - image restoration ƒ  Physics - electron microscopy  ƒ Astronomy, biology, nuclear medicine, law enforcement, defense, industrial applications

Examples of fields that use DIP I.Gamma ray imaging Major uses of imaging based on gamma rays include nuclear medicine and astronomical observations. In nuclear medicine, the approach is to inject a patient with a radioactive isotope that emits gamma rays as it decays. Images are produced from emissions collected by gamma ray detectors. Positron emission tomography(PET) The patient is given a radioactive isotope that emits positrons as it decays. When a positron meets a electron, both are annihilated and two gamma rays are given off. These are detected and a tomographic image is created using the basic principles of tomography.

Examples of fields that use DIP II. X-ray Imaging (oldest source of EM radiation)  X-rays for medical and industrial imaging are generated using an x-ray tube, which is a vacuum tube with a cathode and anode.  The cathode is heated, causing free electrons to be released.  These electrons flow at high speed to the positively charged anode.  When the electron strike a nucleus, energy is released in the form x-ray radiation.  The energy(penetrating power) of the x-rays is controlled by a current applied to the filament in the cathode.

IV. Imaging in the ultraviolet band When it comes to ultraviolet (UV) imaging, it’s important to distinguish between UV light and UV-fluorescence imaging. Although they both use UV lighting, they’re entirely different. UV imaging starts with passing the emission of a UV-emitting LED, lamp or diode, or looking at a subject illuminated with UV light that’s reflected off the item being inspected. The reflected UV light is then captured by the camera. The wavelength of the UV light is not converted or shifted in this process. to be achromatic, significantly lowering cost. In contrast, UV-fluorescence imaging also requires illuminating a surface with UV light, but the fluorescent material absorbs the UV light and electrons are released, causing the material to radiate light at a longer wavelength. The light emitted during this process is usually in the visible range and, in industrial applications, it will usually be blue light. In this type of reaction, light energy in will always exceed light energy out.

Imaging in the ultraviolet band cont. True ultraviolet (UV) imaging inspection isn’t used often in machine vision. However, as UV-sensitive cameras and UV- emitting light sources, particularly LED lighting, have become widely available and less costly, new applications are emerging. Monochromatic UV sources, such as lasers and LEDs, are desirable in machine vision applications because when paired with appropriate Band pass Filters, camera optics don’t need to be achromatic, significantly lowering cost. mages formed with monochromatic illumination are always sharper than images made with broader UV sources, and capability naturally increases as the wavelength used to image the item being inspected is shortened. When using UV illumination, smaller features can often be formed and detected easier and more accurately. This is why monochromatic UV (excimer) lasers and optical imaging are used in producing almost all integrated circuits today.

Examples of fields that use DIP III.Imaging in the visible and infrared bands Infrared band often is used in conjunction with visual imaging. The applications ranges from light microscopy, astronomy, remote sensing industry and law enforcement. E.g. Microscopy- the applications ranges from enhancement to measurement Remote sensing-weather observation from multispectral images from satellites Industry-check up the bottle drink with less quantity Law enforcement – biometrics

Examples of fields that use DIP Imaging in the ultraviolet band When it comes to ultraviolet (UV) imaging, it’s important to distinguish between UV light and UV- fluorescence imaging. Although they both use UV lighting, they’re entirely different. UV imaging starts with passing the emission of a UV-emitting LED, lamp or diode, or looking at a subject illuminated with UV light that’s reflected off the item being inspected. The reflected UV light is then captured by the camera. The wavelength of the UV light is not converted or shifted in this process.

Fundamental steps in digital image processing 1.Image Acquisition: This is the first step or process of the fundamental steps of digital image processing. Image acquisition could be as simple as being given an image that is already in digital form. Generally, the image acquisition stage involves pre-processing, such as scaling etc. 2. Image Enhancement: Image enhancement is among the simplest and most appealing areas of digital image processing. Basically, the idea behind enhancement techniques is to bring out detail that is obscured, or simply to highlight certain features of interest in an image. Such as, changing brightness & contrast etc. 3. Image Restoration: Image restoration is an area that also deals with improving the appearance of an image. However, unlike enhancement, which is subjective, image restoration is objective, in the sense that restoration techniques tend to be based on mathematical or probabilistic models of image degradation.

Fundamental steps in digital image processing cont. 4. Color Image Processing: Color image processing is an area that has been gaining its importance because of the significant increase in the use of digital images over the Internet. This may include color modeling and processing in a digital domain etc. 5. Wavelets and Multi-Resolution Processing: Wavelets are the foundation for representing images in various degrees of resolution. Images subdivision successively into smaller regions for data compression and for pyramidal representation. 6. Compression: Compression deals with techniques for reducing the storage required to save an image or the bandwidth to transmit it. Particularly in the uses of internet it is very much necessary to compress data.

Components of an image processing system 1. In sensing, two elements are required to acquire digital images. The first is physical device that is sensitive to the energy radiated by the object we wish to image. The second called a digitizer, is a device for converting the output of the physical sensing device into digital form. 2. Specialized image processing hardware usually consists fo the digitizer plus hardware that performs other primitive operations such as arithmetic and logical operations (ALU). Eg. Noise reduction. This type of hardware sometimes is called a fron end subsystem. 3. The computer is an image processing system is a general purpose to supercomputer 4. Software which include image processing specialized modules that performa specific tasks 5. Mass storage capability is a must in image processing applications. 6. Image displays in use today are mainly color tv monitors. 7. hardcopy devices for recording images include laser printers, film cameras, inkjet units and cdrom 8. Networking for communication