■Image Engineering Laboratory
03/1981, D.Eng., The University of Tokyo
03/1985, M.Eng., Kanagawa University
- 1. Signal and image processing for intelligent capturing systems for high-resolution, high-quality moving image sequences.
- 2. Nonlinear intelligent signal and image processing based on nonlinear partial differential equations.
- 3. Image sensing system mimicking the HVS (Human Visual System),
- 4. Statistical modeling of a moving image sequence and its application to moving image processing.
- 5. Intelligent image restoration based on the concept of sparse coding,
- 6. Super-resolution color-image restoration with redundant image transform and color shrinkage.
Image electronics and image processing
Consumer demand for higher-quality image-information systems is increasing. In Japan, ultra-high-definition TV broadcasting, such as 4K or 8K TV, will start in the near future and is expected to launch globally shortly after that, and thus demand for ultra-high-definition image content will rise. We are involved in the research and development of various technologies that will form the foundations of the ultrahigh-definition digital image era. At present, we are working on the following research projects.
- 1. Intelligent ultra-high-definition image capturing method mimicking the human visual system.
- 2. Intelligent high-resolution image restoration based on the concept of sparse coding.
- 3. Super-resolution image restoration for image magnification and decompression of degraded compressed image data. Thus, we are developing technologies for capturing and restoring high-quality images.
- 1) T. Komatsu, T. Ken and T. Saito, “Video restoration with 3-D mean-separation-type short-time DFT,” IEICE Transaction on Information and Systems, vol.J100-D, no.9, Sept. 2017.
- 2) T. Komatsu, S. Kondou and T. Saito, “Restoration of a Poisson-Gaussian color moving-image sequence under extremely-low-illumination with virtual multiplex imaging and super-resolution deblurring,” IEICE Transaction on Information and Systems, vol.J99-D, no.9, pp.879-883, Sept. 2016.
- 3) T. Komatsu, S. Kondou and T. Saito, “3-D Redundant DCT restoration method for MPEG-compressed video,” IEICE Transaction on Information and Systems, vol.J99-D, no.9, pp. 874-878, Sept. 2016.
- 4) T. Shikano, T. Komatsu and T. Saito, “De-blurring method of a landscape image with its range data,” IEICE Transaction on Information and Systems, vol.J97-D, no.9, pp.1459-1462, Sept. 2014.
- 5) T. Kobari, T. Komatsu and T. Saito, “Color-image denoising with adaptive shrinkage based on a mixture Gaussian distribution model,” IEICE Transaction on Information and Systems, vol.J96-D, no.9, pp.1989-1992, Sept. 2013.
- 6) R. Kobayashi, T. Komatsu and T. Saito, “Restoration of Poissonian random images based on a statistical model,” IEICE Transaction on Information and Systems, vol.J96-D, no.9, pp.1993-1997, Sept. 2013.
- 7) T. Saito, Y. Ueda and T. Komatsu, “Color shrinkage for color-image sparse coding and its applications,” IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, vol. E94-A, no.2, pp. 480-492, Feb. 2011.
Affiliated Academic Organizations
T. Saito:IEICE, ITE, IPS of Japan, IEEE.
T. Komatsu: IEICE, ITE.
|◯ Professors: 1||◯ Research Associates: 1|
|◯ Postgraduates: 2||◯ Undergraduates: 15|
Facilities: Laser range finder, three-eye video camera system, 3D-projector
Number of graduates: B. Eng.: 391, M. Eng.: 80, D. Eng.: 2