Computational Photography

Third semester: UB, Bordeaux
Class Type
Lecture, Practical
Type of the exam
Labs, Oral presentation, Projects
Prerequisites (if exist)
Basic image processing, C and matlab programming
Dr. Aurélie Bugeau, Associate Professor, Dr. Edoardo Provenzi, Full Professor
Hours per week


This course focuses on methods for image manipulation and computational photography with application to High dynamic Range image, texture synthesis, inpainting / Image and video completion, denoising, object segmentation, image retargeting, etc.

The nature of light and its interaction with matter
A brief recap on electromagnetic waves, light, radiometry
Image formation models, Bayer pattern, demosaicking
Reflectance retrieval models based on white patch and gray world assumptions
Physiology of the eye and photometry
Eye optical elements
Retinal cells and their response to light
Metrology of photometric units
light acquisition: Human visual perception
Intensity contrast perception: Weber-Fechner’s and Stevens’ laws
Spatial contrast perception: the importance of the surround
Chromatic adaptation and color constancy
High Dynamic Range (HDR) imaging
A brief history of HDR imaging
Debevec-Malik’s algorithm to generate HDR images
The problem of motion
An overview on tone mapping algorithms
Patch-based image editing
Template Matching
Non parametric texture synthesis
Examplar-based inpainting
Fast nearest neighbor search
Image quilting, seam carving
Seam carving with dynamic programming
Image quilting with graph representation
Graph Cuts
Image blending, compositing
Image blending, Poisson image editing

Recommended Reading

There is no textbook for this class. Mandatory and optional readings will be suggested for each lecture individually among which:
– A.A. Efros and T.K. Leung,Texture Synthesis by Non-parametric Sampling, ICCV, 1999
– Y. Boykov and M.-P. Jolly, Interactive Graph Cuts for Optimal Boundary & Region Segmentation of Objects in N-D Images, ICCV, 2001.

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