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Image_Processing - DSPClub CepstrumPresents...

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    DSP Club Cepstrum Presents-                      Talk on Image Processing       Speakers: Turaga Pavan                  Nishant Mohan
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Purpose of Talk Preview of the field Starting point for future IPians Knowledge of Modern Image  Processing
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Plan of Talk Basics of image storage Major issues in IP Some Matlab functions Interesting Readings What’s on in IIT-G
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Image as a Signal Image – 2D information of light intensity. Information Source, Focussing Agent,  Sensor. Nearly always digital.
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Digital Images 2D array of numbers – representing  intensity. Numbers stored as bits.  Generally used – 8 bit/pixel, 16 bit/pixel.
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Gray Scales Low intensity-  Lower gray scale  value Highest possible  gray level=2 n -1
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Color Image Primary Colors- Red, Green, Blue. All colors can be formed by specifying  relative values of R,G & B components. Each component is separately stored  like gray levels (3D matrix). Hence color images can occupy 3 times  the space required by b/w images.
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Image Storage Formats Popular formats : BMP, JPG, GIF, TIFF  etc Different formats – Different levels and  techniques of image compression Commercial Issues -  Registered  formats 
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Compression Resolution of standard medical images  is : 1024x1024 A complete data set may contain 100  slices Storing as 8-bit/pixel Computer memory required = 800 Mb Hence compression is practically must
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How to Compress Psycho-visual redundancy Spatial redundancy Mathematical models – Information  theoretic redundancies Transform coding
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Matlab Function imread : reads image data in major  formats imwrite : writes image from given data imshow : shows image in matlab window
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Till Now ……… How to look at image as a signal Need for compression Why is compression possible                                Q?
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Challenges in Image  Processing Image Enhancement Image Segmentation Image Understanding – retrieving  required information from an image.
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Image Enhancement Common Problems with images – Noise Blur Low Contrast
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