Acknowledgment
People who have contributed to this database:

Bilel Sdiri, Borhen Eddine Dakkar, Lynda Chami, Asjad Amin, Ashiq Hussain and the 23 participants . Thanks to Shaohua Chen who provided the matlab code of MRETINEX..

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Laparoscopic Video Quality (LVQ) Database – direct link https://drive.google.com/file/d/1SoONeacp9vvihTY7zmWssG_cnVzx16oq/view
Laparoscopic Video Quality Database (LVQ) contains 10 reference laparoscopic videos each of 10 seconds duration which are distorted with 5 different distortions at 4 different levels. The distortions include some of those often encountered during the laparoscopic surgery namely defocus blur, motion blur, uneven illumination, smoke and noise. The subjective scores in the database were obtained both from non-medical observers (29 in total) as well as medical observers (9 in total).

Lead Principal Investigator (LPI)  : Azeddine Beghdadi

Co-PIs : Khan, Z.A., , Cheikh, F.A., Kaaniche, M., Pelanis, E., Palomar, R., Fretland, Å.A., Edwin, B. and Elle, O.J

Citation : Khan, Z.A., Beghdadi, A., Cheikh, F.A., Kaaniche, M., Pelanis, E., Palomar, R., Fretland, Å.A., Edwin, B. and Elle, O.J., 2020, March. Towards a video quality assessment based framework for enhancement of laparoscopic videos. In Medical Imaging 2020: Image Perception, Observer Performance, and Technology Assessment (Vol. 11316, p. 113160P). International Society for Optics and Photonics.

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VQUAD

Open dataset for video quality assessment in the context of video-surveillance

VQUAD is  dataset dedicated to video quality assessment in the context of video surveillance. This database consists of a set of common distortions at different levels of annoyance. The subjective tests are performed using a classical pair comparison protocol with some new configurations.

This new database referred to as VQUAD, contains 14 color full-HD (1920,1080 pixels) videos and 224 distorted videos. The database is built with free-use youtube videos from live streams and some common videos used by the video processing community from Virat Database. Youtube videos are provided by a video surveillance equipment’s provider from Netherlands called WebCam.NL.

Database link:

Lead Principal Investigator (LPI)  : Azeddine Beghdadi

Co-PIs : I. Bezzine, Z. A. Khan, N. Almaadeed, M. Kaaniche, S. Almaadeed, A. Bouridane, F. Alaya Cheikh

Citations : I. Bezzine, Z. A. Khan, A. Beghdadi, N. Almaadeed, M. Kaaniche, S. Almaadeed, A. Bouridane, F. Alaya Cheikh, »Video quality assessment dataset for smart public security systems », in the proceedings of the 23rd International IEEE – INMIC2020, Bahawalpur, Pakistan, 5-7 November 2020,

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Free Image Processing and Analysis  software

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MRETINEX

« Natural Enhancement of Color Image » by S. Chen, A. Beghdadi, —  Code and demo available at http://www.ipol.im/pub/pre/252/. —–  details are published in  Eurasip Journal on Image and Video Processing, Volume 2010 (2010), Article ID 175203, 19 pages,doi:10.1155/2010/175203, PDF

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TRAITIM

Traitim : Some image processing tools (low-level treatments) developed with my colleague and friend Alain Le Négrate.

This software is free. I would appreciate if you could cite the references related to this soft. The details of some methods developed in this software are published in :

1. A. Beghdadi, A. Le Négrate, P. Viaris De Lesegno.,  » Entropic thresholding using a block source model  » , Computer Vision Graphics and Image Processing : Graphical Models and Image Processing, Vol.57, N°.3, May, pp.197-205, 1995
2. A. Le Négrate, A. Beghdadi and H. Dupoisot., « An Image Enhancement Technique and its Evaluation through Bimodality Analysis « , Computer Vision Graphics and Image Processing : Graphical Models and Image Processing, Vol. 54, N°. 1, Jan. 1991, 13-22.
3. A. Beghdadi, A. Le Négrate. » Contrast Enhancement Technique Based on the Local Detection of Edges « , Computer Vision Graphics and Image Processing, 46, 1989, 162-174.
4. A. Beghdadi, A. Constans, P. Gadenne, J. Lafait,  » Optimum Image Processing for Morphological Study of Granular Thin Films « , Rev. Phys. Appl., Jan. 1986, 73-80

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 SMARTFLOW

Smartflow : displacement field estimation and some image processing tools developed with my former PhD student Jérôme Monteil

This software is free. I would appreciate if you could cite the references related to this soft. The details of some methods developed in this software are published in :

1. A. Beghdadi, M. Mesbah, J. Monteil, « A Fast Incremental Approach for Accurate Measurement of the Displacement Field « , Image and Vision Computing Journal, 21, (2003), pp.383-399 (PDF)
2. J. Monteil, A. Beghdadi,  » A New Interpretation and improvement of the Nonlinear Anisotropic Diffusion for Image Enhancement « , IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.21, N°9,1999, 940-946. (PDF)
3. A. Beghdadi, M.-F. Auclair-Fortier and J. Monteil, « Tracking of Image Intensities Based on Optical Flow : An Evaluation of Nonlinear Diffusion Process », Proceedings of the 2nd IEEE International Symposium on Signal Processing and Information Technology, pp.691-696, Marrakesh, Morocco, 18-21 December 2002.
4. J. Monteil, A. Beghdadi,  » A new adaptive nonlinear anisotropic diffusion for noise smoothing « , Procedings of IEEE International Conference on Image Processing, Chicago October 1998, Vol. 3, pp. 254-258  (PDF)
5. N. Ben Amar, A. Beghdadi and P. Viaris De Lesegno,  » An All-Digital Method for Accurate Measurements of Mechanical Deformations « , Scanning, The Journal of Scanning Microscopy, Vol.18, 3, (1996),pp.327-330.
6. J. Monteil, A. Beghdadi, P. Viaris de Lesegno, « Mesure du champ de déformation par une technique incrémentale de flux optique »- la Revue de Métallurgie – CIT , tome 97, N°.2, février 2000, pp.229-238.