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IMAGE PROCESSING

Explore digital image processing fundamentals, techniques, and applications in this 20-hour lecture series. Learn about image formats, enhancement, restoration, and various processing methods. Discover real-life examples of image processing applications.

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IMAGE PROCESSING

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  1. IMAGE PROCESSING Ferda Ernawan, Ph.D Postgraduate Program of Dian Nuswantoro University Email: ferda.ernawan@yahoo.com

  2. Administrative • Course Implementation • Lecture: 2 hrs per week for 10 weeks (Total=20 hrs) • Course Evaluation:

  3. Lecture 1 Introduction

  4. References “Digital Image Processing”, Rafael C. Gonzalez & Richard E. Woods, Addison-Wesley, 2002 • Bahanmateri yang diambildaribukutersebut

  5. Contents • Sub pokokpembahasanmeliputi: • Pengertian digital image? • Pengertian digital image processing? • Contoh digital image processing dalamkehidupansehari-hari • Aspect of Image Processing • Fundamental step in digital image processing • Matlab as a research tools for image processing and applications • Characteristic of a good paper in term of image processing and applications • Penjelasan assignment 1

  6. Pengertian Digital Image • Sebuahgambar digital adalahrepresentasidarigambarduadimensisebagaihimpunanterhinggadarinilai digital, ataubiasadisebutelemengambaratau pixel.

  7. 1 pixel Digital Image • Nilaisebuah pixel biasanyamerupakantingkatabu-abu, warna, tingkatkecerahanataukekeruhan, dll. • Digitalisasisebuah image adalahmenggambarkansebuahkejadiannyata.

  8. Digital Image Nilaisuatu pixel merupakan single number darisuatuintensitasgambaratauwarnagambar. Digital Image merupakan multidimensional array dariintensitasgambaratauwarnagambar.

  9. Digital Image • 1 sample per point (Black & White or Grayscale) • 3 samples per point (Red, Green, and Blue) • 4 samples per point (Red, Green, Blue, and “Alpha”)

  10. Image Format • GIF (Graphic Interchange Format) • PNG (Portable Network Graphics) • JPEG (Joint Photographic Experts Group) • TIFF (Tagged Image File Format) • PGM (Portable Gray Map) • FITS (Flexible Image Transport System) • BMP (Bitmap)

  11. Digital Image Processing • Digital Image Processing fokuspadaduatugasutama: • Peningkataninformasigambaruntukinterpretasimanusia • Pengolahan data image untukpenyimpanan, transmisi, danrepresentasiuntuk autonomous machine perception.

  12. Digital Image Processing • Penggunaanteknikpengolahancitra digital telahmeningkatdan image processing application sekarangtelahdigunakanuntuksemuajenispekerjaanpadasemuajenisbidang, misalnya: • Image enhancement dan restoration • Artistic effects • Medical visualisation • Industrial inspection • Law enforcement • Human computer interfaces

  13. Contoh Image Enhancement • Salahsatupenggunaan yang paling umumdariteknik Digital Image Processing yaitumeningkatkankualitas, remove noise, dansebagainya.

  14. Contoh Image Restoration Image yang terdegradasi The result of image restoration

  15. ContohEfekArtistik • EfekArtistikdigunakanuntukmembuatgambarlebihmenarikdanuntukmenambahkansuatuefekkhusus.

  16. Contoh: Medicine • Ambilirisandari scan hati, danmenentukanbatasbatasantarajenisjaringan • Gambardenganabu-abumewakilitingkatkepadatanjaringan. • Gunakan filter yang cocokuntukmenyorottepi. Original Image of a Heart Edge Detection Image

  17. Contoh Industrial Inspection • Manusiasebagai operator memerlukanbiayamahal. • Mesindapatmelakukanpekerjaanlebihcepat, dansistemindustrisepertiitusudahdigunakandalamsemuajenisindustri.

  18. Contoh Law enforcement • Teknikpemrosesangambardigunakansecaraluasolehpenegakhukum • Monitoring nomorpelatmobildalammemonitorkecepatan / sistemtolotomatis • Pengenalansidikjari • Peningkatan CCTV gambar

  19. Contoh GIS • SistemInformasiGeografis • Digital image processing digunakansecaraekstensifuntukmemanipulasicitrasatelit.

  20. Fundamental step in digital image processing Color image processing Wavelets and multi resolution processing Image Compression Morphological Processing Segmentation Image Restoration Knowledge base Representation & Description Image Enhancement Object Recognition Image Acquisition Problem Domain

  21. Fundamental step in digital image processing Color image processing Wavelets and multi resolution processing Image Compression Morphological Processing Segmentation Image Restoration Representation & Description Image Enhancement Object Recognition Image Acquisition Problem Domain

  22. Fundamental step in digital image processing Color image processing Wavelets and multi resolution processing Image Compression Morphological Processing Segmentation Image Restoration Representation & Description Image Enhancement Object Recognition Image Acquisition Problem Domain

  23. Fundamental step in digital image processing Color image processing Wavelets and multi resolution processing Image Compression Morphological Processing Segmentation Image Restoration Representation & Description Image Enhancement Object Recognition Image Acquisition Problem Domain

  24. Fundamental step in digital image processing Colour image processing Wavelets and multi resolution processing Image Compression Morphological Processing Segmentation Image Restoration Representation & Description Image Enhancement Object Recognition Image Acquisition Problem Domain

  25. Fundamental step in digital image processing Color image processing Wavelets and multi resolution processing Image Compression Morphological Processing Segmentation Image Restoration Representation & Description Image Enhancement Object Recognition Image Acquisition Problem Domain

  26. Fundamental step in digital image processing Color image processing Wavelets and multi resolution processing Image Compression Morphological Processing Segmentation Image Restoration Representation & Description Image Enhancement Object Recognition Image Acquisition Problem Domain

  27. Fundamental step in digital image processing Color image processing Wavelets and multi resolution processing Image Compression Morphological Processing Segmentation Image Restoration Representation & Description Image Enhancement Object Recognition Image Acquisition Problem Domain

  28. Fundamental step in digital image processing Color image processing Wavelets and multi resolution processing Image Compression Morphological Processing Segmentation Image Restoration Representation & Description Image Enhancement Object Recognition Image Acquisition Problem Domain

  29. Fundamental step in digital image processing Color image processing Wavelets and multi resolution processing Image Compression Morphological Processing Segmentation Image Restoration Representation & Description Image Enhancement Object Recognition Image Acquisition Problem Domain

  30. MATLAB as research tool for Image Processing and Application

  31. Matlab • The basic data structure in Matlab is the array, and the operation is sequence, like C programming. • Matlab stores image as two dimensional array (matrices), each element of the matrix represents a single pixel in the displayed image. • By default, Matlab stores the data in array of class double.

  32. What is Image Processing Toolbox? • Image processing toolbox is collection of function of Matlab numeric computing environment. • toolbox functions implement specialized image processing algorithm.

  33. Image Processing Toolbox • Geometric operations • Neighborhood and block operation • Linier filtering and filter design • Transformation domain • Image analysis and enhancement • Binary image operations • Region of interest operation.

  34. Image Type in the toolbox • The Image Processing toolbox supports basic type of image, for example: • Indexed images • Binary images • RGB images

  35. RGB Image • In Matlab , the red, green, and blue component of RGB image reside in single m-by-n-by-3 array. • m and n are the number of rows and columns of pixels in the image, and the third dimension consists of red, green, and blue intensity values. • Each pixel in the image, the red, green, and blue elements are combine to create the pixel’s actual color.

  36. RGB Image An RGB array can be: • Class double, in this case it contains values in the range [0,1] • Class uint8, in this case the data range is [0,255]

  37. What should you do with image data? • Reading in image data from files, and writing image data out to file. • Converting images to other image types. • Working with uint8 arrays in Matlab and the Image Processing toolbox.

  38. Reading images You can use the Matlab function to read image data from files. Imread(‘filename’) Imread function can read these graphics file formats: • TIFF (Tagged Image File Format) • JPEG (Join Photographics Expert’s Group) • HDF (Hierarchical Data Format) • BMP (Windows Bitmap) • XWD (X-Window Dump)

  39. Writing Images • To write image data from Matlab to a file, you can use imwrite function. Imwrite can write the same file formats that imread reads. • See the references entire for imread and imwrite for more information about these function. • In addition, you can use imfinfo function to return information about the image data in a file.

  40. Converting Image

  41. Converting Image

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