Multimedia Signal Processing Unit-Books Pdf

MULTIMEDIA SIGNAL PROCESSING UNIT
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Introduction, Digital image video processing a new domain and technology. Mathematics of information,Signal processing,Electronic optronics systems. Computer sciences and micro processors VLSI DSP,Lots of methods. ad hoc founded as well,Needs of methodology,Widespectrum of applications. 2005 D BARBA 2, When we speak of digital image processing we mean the set of techniques used to.
modify a digital image in order to improve it in terms of quality or to reduce its size in. terms of bits compression encoding or to get information out of it Processing digital images. is a new sector of knowledge which has quickly developed thanks to the emergence of new. information technologies It relies mainly on the mathematics linked to information signal. processing electronic systems and the advance in microprocessor computation capacities. particularly those that have been exclusively developed for signal processing and which offer. high computation speed and capacity DSP etc, As digital image processing is in its early stages and its scope of application is quite spread it. has quickly become apparent that a methodology must be created and the domains of. application separated out Image processing can now be seen as four distinct fields of action. analysis synthesis coding and quality enhancement, To start with a description of these four domains will allow us to better understand what. image processing really is Following this we will look at how to obtain the digital images. by digitization of analog images that we wish to process. Introduction,A picture is worth one thousand words. and a video is worth one thousand sentences,2005 D BARBA 3. We come in contact with all sorts of images in our daily environment photographs of. landscapes of people computer generated drawings and paintings images from medical. radiology satellite images and so on Some of these images such as via satellites and for. medicine cannot be directly observed while others have characteristics that can be extracted. automatically stored and sent The processing that could be carried out on these images is. highly varied as the images we meet in our environment are also varied by their nature and. properties as well as the scenes they describe They are all different but evidently it is not. conceivable to create a specific type of processing for each one This has led to a. classification of image processing that does not rely on image characteristics but rather on the. objective of the processing We can distinguish four types of domains of application for the. digital image processing,restoration and enhancement image.
image analysis,image coding with data compression,image synthesis. Image Video processing types 4,Enhancement Data compression. Restoration,Vision model,System Algorithmic,Modeling Artificial Intelligence. Image video,processing,Analysis Synthesis,2005 D BARBA 5. Let s now look in detail at the four fields of action linked to digital image processing. Enhancement and restoration, Let s consider an observed image I0 with which we associate a signal s0 that we model.
as s0 f su d b, where su is the usable image signal obtained from an ideal image without any loss. d is the distortion function which operates on the ideal image geometric distortions. b is noise, f is an observation function dependant of these two signals and of the distortion. The processing carried out on I0 which will output the transformed image IT must enable the. information contained in IT to be used in a more efficient manner than the information in the. directly observed image I0 If a change occurs in the presentation characteristics of the image. we can talk of an enhancement process whereas if there is a partial inversion in the quality. loss we can talk of a restoration process for example 2D linear filters 2D adaptive filters. Image Video processing types 4,Enhancement Data compression. Restoration,Vision model,System Algorithmic,Modeling Artificial Intelligence. Image video,processing,Analysis Synthesis,2005 D BARBA 5.
Image analysis, This refers to partially or fully describing the scene from the observed image objects. detection object dimensions position in space etc, Classically this analysis process takes place in 3 successive stages. pre processing and extraction of the characteristic traits. classification and pattern recognition, description and possibly interpretation of the image content. Note however that image analysis also varies depending on the support medium the problems. raised by the analysis of 2D images of 3D images or of moving images are quite numerous. with a special attention to moving images due to the techniques used in that case and the. nature of the required objectives,Image Video processing types 4. Enhancement Data compression,Restoration,Vision model.
System Algorithmic,Modeling Artificial Intelligence. Image video,processing,Analysis Synthesis,2005 D BARBA 5. Image coding with data compression, The basis for representing a digital image is a rectangular 2D table of elements called. pixels This implies to handle and memorize a large amount of pixels For a simple grayscale. image typically 512 512 pixels 256 000 pixels and 8 bits per pixel must be memorized to. obtain a good resolution 8 bits to code one pixel which gives per pixel a number of 28 256. possible values For high resolution color images or for moving images the number of bits. necessary for image representation quickly becomes enormous to store or send it. Encoding an image aims to obtain a representation of that image that requires a greatly. reduced number of bits in comparison with the original image representation. To measure this reduction we use a compression rate defined as. number of bits representing the basic image representation. number of bits representing the image after encoding. This rate must be higher than 1 for real compression to take place. As the number of bits for the basic image representation is fixed the compression rate is in. fact inversely proportional to the number of bits representing the image after encoding If you. want to make an exact reconstruction of the image after decoding you need to use reversible. encoding This creates a constraint that means that the compression rate is often rather low. To increase the compression rate significantly you need only to rely on a representation that. is visually exact In this case the human eye will perceive no difference between the original. image and the image that is reconstituted after decoding In addition the complexity of the. encoding decoding must be limited Encoding a digital image involves finding a healthy. balance between the compression rate that will be high enough to make data storage and. transmission easier but that will not unduly affect the picture quality and simultaneously. keeping in mind that decoding complexity must be restrained. Image Video processing types 4,Enhancement Data compression. Restoration,Vision model,System Algorithmic,Modeling Artificial Intelligence.
Image video,processing,Analysis Synthesis,2005 D BARBA 5. Image synthesis, The goal of this is to reconstruct an image that resembles an image from the simulated. scene from a description of the scene the objects making it up its lighting characteristics. e g lightening orientation intensity as well as the capture device CCD or CMOS camera. etc This reconstructed scene may resemble reality or be purely fictional The first. applications concerning image synthesis were oriented towards training simulators flight and. vehicle simulators before involving out into other domains audiovisual cinema art etc. We should point out that image processing also relies on studies linked to the structure of. processing machines An image contains a significant amount of data In fact for a moving. image there are N M P samples per second to process N dots per line M lines and P images. per second Image processing requires powerful calculation capacity It needs high. performance architectures with high degrees of parallelism and significant processing speeds. Digital image processing has just been presented in accordance with the four main. domains of application We can now look at this from another angle by concentrating of the. nature of the processing results,General view of Image Video processing. Data Pattern Object,Parameters Pattern Recognition. measurement,Image Video,Enhancement,2D 3D 2D t 3D t.
Image video,Restoration synthesis,Coding Image video. Decoding Analysis,Image video Description,2005 D BARBA 6. We can characterize image processing not simply in terms of its domains of. application but also according to the nature of the results that will be put out There can be. two types of input an image or a description,From an image input. The output may be,image type, This is the case with image coding for data compression image enhancement. and restoration of poor quality images these three have already been presented. This is the case when you make an elementary image analysis You are. interested in the spatial dimensions of an object in the scene its position or its. pattern type, This is also a case of image analysis but a more elaborate one This involves.
extracting and recognizing the objects observed in the scene. scene description type, This is also a possible output for an image analysis but in the most advanced. version The image is entirely broken up so that each object present in the. scene can be recognized The scene is described in its totality and can be. interpreted,From a description input, For the output the only expected type is an image The domain of application involved is. image synthesis We wish to reconstruct the image according to a given description What. objects are present What are their dimensions Where are they in the scene How are they. lit What are the parameters focal length viewing angle etc of the camera doing the. You have now studied image processing from two different aspects these aspects are. nevertheless strongly interconnected We can now go on to look at the characteristics of the. signal that we wish to process the image,Basic Image Video Properties. Image video signal is a 2 D 2 D t scalar vectorial signal which is. Non stationary,Non Gaussian,Non isotropic,Two image or three video main features. Contours abrupt change in some important characteristics. Texture spatial variation of the 2 D signal apart its local mean value. mean value texture description,Edges are locally 1 D signals.
Motion in case of video time varying image sequence. 2005 D BARBA 7, An image is a 2D scalar grayscale image or vectorial color image for example signal. Video which is a succession of images ordered temporally is a 2 D t t time scalar gray. scale video or vectorial color video signal,The Image signal is complex because it is. non stationary its contents in space frequencies change with the space. coordinates, non Gaussian its statistical properties do not follow a Gaussian probability law. non isotropic the properties of the image signal are not the same ones with the. orientation e g in the images taken on the ground the horizontal and vertical. directions are more frequent for contours than the oblique directions. The classical methods and tools used in signal processing are often designed for stationary. Gaussian or isotropic signals e g Discrete Fourier Transform They cannot be directly. applied to images, Incidentally images are mainly characterized by two types of element namely contour and. Contours are abrupt change of important characteristics from an area A to an area. B of a scene average value texture description The edges can be locally. considered as 1D signals, Textures are spatial variation of the 2D signal apart its local mean value.
Motion of the objects in a scene involves temporal modifications in the successive. frames of a video, Now you have seen a general overview of images and digital image processing In the. next part of this chapter we will look at methods for representing images digitizing and. encoding which must be used in order to carry out digital processing We will also see some. concrete examples of results relating to the domains of application that we explored earlier. MULTIMEDIA SIGNAL PROCESSING,Examples of Image Processing. Images and Videos Analysis,2005 D BARBA 1, The four major domains of application for image processing have been globally. presented what are the issues what are the objectives what methods to use and which. tools We will now look more closely at some concrete applications derived from these. different domains,Image and video analysis,Objectives. Objects detection and extraction segmentation,Objects of interest.
Pattern recognition,Object classification object identification. Scene analysis and interpretation,Relational,Quantitative description. Qualitative description,2005 D BARBA 2, The first domain that interests us is image analysis This covers a large number of. potential applications and is probably the domain for which there is the greatest variety of. examples medical analysis classification of chromosomes automatic reading signature. As digital image processing is in its early stages and its scope of application is quite spread it has quickly become apparent that a methodology must be created and the domains of application separated out Image processing can now be seen as four distinct fields of action analysis synthesis coding and quality enhancement

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