Advanced Multimedia Lecture 4 PDF

Advanced Multimedia Lecture 4  Computer imaging It’s defined as the acquisition and processing of visual information by computer. The ultimate receiver of information is: o Computer o Human visual system So we have two categories:- o Computer vision o Image processing ...

Advanced Multimedia Lecture 4  Computer imaging It’s defined as the acquisition and processing of visual information by computer. The ultimate receiver of information is: o Computer o Human visual system So we have two categories:- o Computer vision o Image processing Computer vision and image processing In Computer vision: o The processed output images are for use by computer. In Image processing: o The output images are for human consumption.  Computer vision One of the computer vision fields is image analysis. It involves the examination of image data to facilitate solving a vision problem. Image analysis has 2 topics: o Feature extraction: acquiring higher level image information o Pattern classification: taking these higher level of information and identifying objects within the image  Image Processing image in image out Image Analysis image in measurements out Image Understanding image in high level description out  Image Processing Common image formats include: sample per point (B&W or Gray scale) samples per point (Red, Green, and Blue) samples per point (Red, Green, Blue, and “Alpha”, Opacity) RGB Coloring System  RGB Coloring System Color image: The number of color values in it is equal 224 equal 16,777,216 color There are three main colors and they are RED,BLUE and GREEN each pixel in color image carries three values ,it is combination of the three colors to represent a new color. This means that a single color has a size of 8bits. Each color has values from 0 to 255,that is the red color has 255 different values (from light to dark)  RGB Coloring System In a color image, the image is represented as three- dimensional matrix as shown in the figure below.  ‫العمق‬ ‫المعــادلة‬ ‫معلومات‬ ‫بت ‪1‬‬ ‫لون ‪21 = 2‬‬ ‫تسمي صورة أبيض وأسود )‪(Black and White Image‬‬ ‫بت ‪4‬‬ ‫لون ‪24 = 16‬‬ ‫تستخدم في الشاشات منخفضة الدقة‬ ‫بت ‪8‬‬ ‫لون ‪28 = 256‬‬ ‫تسمي صور ملونة مفهرسة )‪(Indexed Color Images‬‬ ‫)‪ (Grey‬بت ‪8‬‬ ‫لون ‪28 = 256‬‬ ‫تسمي صور درجات الرمادي )‪(Grayscale image‬‬ ‫بت ‪16‬‬ ‫لون‪216 = 65536‬‬ ‫تسمي تنسيق ألوان عالي )‪(High Color Format‬‬ ‫(‪ )B‬أزرق بت‪ )G ( 5‬أخضر بت ‪ )R ( 6‬أحمر بت ‪5‬‬ ‫بت ‪24‬‬ ‫لون ‪224 = 16777 216‬‬ ‫تسمي اللون الحقيقي ‪(True Color‬صوره ملونة)‬ ‫لكل لون ‪ 8‬بت أي ‪(R,G,B) 256‬‬ ‫بت ‪32‬‬ ‫‪232‬‬ ‫تستخدم ك قناة ألفا )‪(Alpha Channel‬‬ ‫لون ‪= 4294 967296‬‬  Digital image processing  Digital image processing focuses on two major tasks: – Improvement of pictorial information for human interpretation – Processing of image data for storage, transmission and representation for machine perception ‫فهم االدراك‬  …Digital Image Processing image processing to computer vision can be broken up into low-, mid-and high-level processes. Example: Image Enhancement Example: The Hubble Telescope Example: Medicine  Bitmap Storage The most straightforward way of storing a bitmap is simply to list the bitmap information, byte after byte, row by row. Files stored by this method are often called RAW files.  The amount of disk storage required for any bitmap is easy to calculate given the bitmap dimensions (N x M) and color depth in bits (B). The formula for the file size in K Bytes is: Size (KB) = M*N*B 8*1024 Where N and M are the number of horizontal and vertical pixels, B is the number of bits per pixel.  The following table shows the file sizes of a few bitmap types if they are stored in RAW format. image dimensions colour depth file size 128 x 128 1 bit 2 KB 8 bits 16 KB 24 bits 48 KB 256 x 256 1 bit 8 KB 8 bits 64 KB 24 bits 192 KB 1K x 1K 1 bit 128 KB 8 bits 1 MB 24 bits 3 MB  As can be seen from this table, large 24bit images will result in very large files, this is why compression becomes important. Main Steps in Digital Image Processing  Image Acquisition Acquisition could be as simple as being given an image that already in digital form. Generally , the image acquisition stage involves preprocessing, such as scaling.  Image Enhancement Is among the simplest and most appealing area 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.  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 on mathematical or probabilistic models.  Morphological processing Deals with tools for extracting image components that are useful in the representation and description of shape.  Segmentation processing Procedures that partition an image into parts or objects. In general, the more accurate the segmentation, the more likely recognition is to succeed.  Recognition Is the process that assigns a label to an object based on its descriptors.  Representation and Description Also called feature selection, deals with extracting attributes that result in some quantitative information of interest or are basic for differentiating one class of objects from another.  Compression Deals with techniques for reducing the storage required to save an image, or bandwidth required to transmit it. Example JPEG  Color image processing Is an area that has been gaining in importance because of significant increase in the use of digital images over the Internet. Colors used also as basis for extracting features of interest in an image.