Akıllı Sistemler Mühendisliği Yüksek Lisans Programı

Sayısal Görüntü İşleme(ISI 523)

Ders Kodu Dersin Adı Yarıyıl Teori Uygulama Lab Kredisi AKTS
ISI 523 Sayısal Görüntü İşleme 1 3 0 0 3 6
Ön Koşul
Derse Kabul Koşulları
Dersin Dili İngilizce
Türü Seçmeli
Dersin Düzeyi Yüksek Lisans
Dersi Veren(ler) İsmail Burak PARLAK bparlak@gsu.edu.tr (Email)
Dersin Yardımcıları
Dersin Amacı Digital image processing is among the fastest growing computer technologies. Image and video modalities are considered as complex data structures due to multidisciplinary applications and broad range of file structures. With increasing computer power, it is now possible to do numerically many tasks that were previously done using analogue techniques. The objective of this course is to provide a brief introduction to methodologies applicable to digital image processing and to develop a foundation that can be used as the basis for further study and research in this field.
İçerik • Introduction, Image Representation, Image Encoding
• Intensity Transformations, Geometric Transformations
• Spatial Filtering, Fourier Transform, Short-Time Fourier Transform, Convolution
• Frequency Domain Filtering, Sampling
• Image Restoration, Image Enhancement
• Edge Detection-Sharpening
• Multi-resolution Analysis
• Image Pyramids
• Image morphology
• Wavelets
• Image Compression
• Applications: segmentation, watermarking, recognition
• Deep learning models in image & video
• Advanced topics: Video applications
Dersin Öğrenme Çıktıları
Öğretim Yöntemleri
Kaynaklar Textbook(s):
R. Gonzalez and R. Woods Digital Image Processing, Pearson, 4th Edition, 2018
M. Sonka, V. Hlavac, and R. Boyle, Image Processing, Analysis and Machine Vision, 4th Edition Cengage Learning, 2015

Supplementary Books:
Alberto Fernandez Villan - Mastering OpenCV 4 with Python: A practical guide covering topics from image processing, augmented reality to deep learning with OpenCV 4 and Python 3.7 Packt Publishing, 2019
A. Murat Tekalp - Digital Video Processing (Prentice Hall Signal Processing) 2nd Edition, 2015
Ian Goodfellow, Yoshua Bengio, Aaron Courville – Deep Learning, MIT Press, 2016 https://www.deeplearningbook.org/
Ders İçeriğini Yazdır
Teori Konu Başlıkları
Hafta Konu Başlıkları
Uygulama Konu Başlıkları
Hafta Konu Başlıkları
Başarı Notuna Etki Oranları
  Sayı Katkı Payı
Toplam 0 0
Yarıyıl İçi Çalışmaları
  Sayı Katkı Payı
Toplam 0 0
Numara Program Yeterlilikleri Puan
1 2 3 4 5
Etkinlikler Sayı Süre Toplam İş Yükü
Toplam İş Yükü 0
Toplam İş Yükü / 25 0,00
Dersin AKTS Kredisi 0
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