Angelo Bosco
System Engineer
STMicroelectronics
Advanced System Technology - Catania Lab
Imaging and Mobile Multimedia Group
(IGP & Codecs)
C.V. (English):
He received the degree in
Computer Science in 1997 with a thesis in the field of image processing:
"Automatic analysis of traffic video sequences", supervised by prof.
G. Gallo.
From February 1998 to May 1999 he worked in a software house located in catania:
Proteo.
He joined
STMicroelectronics
in June 1999 as a system engineer in the Digital Still Camera and Mobile
Multimedia Group.
He has been working on different topics, including:
i) noise reduction / defect correction algorithms for cmos sensors both
for still pictures and video.
ii) frame rate up conversion techniques
iii) wavelets.
iv) digital video stabilization
v) face tracking.
Italian C.V.
Publications (Pubblicazioni):
[1]
A. Bosco, M. Mancuso - "Adaptive Filtering For Image
Denoising" - in IEEE Proceedings of ICCE 2001 (International Conference on Consumer
Electronics) (pp.208-209), Los Angeles, June 2001
Abstract: This
paper presents an adaptive image filter that reduces the amount of noise in
images acquired by digital still camera sensors in a Bayer pattern format. The
filter acts mainly on the high spatial frequency components of the image in all
the areas where they are not perceived by the human visual system (HVS); thus it
is an adaptive filter that improves the image quality.
[2]
S. Battiato, M. Mancuso, A. Bosco, M. Guarnera - "Psychovisual and Statistical Optimization of Quantization Tables for DCT Compression
Engines" - In IEEE Proceedings of International Conference on Image Analysis and Processing ICIAP 2001
(International Conference on Image Analysis and Processing) - Palermo, Italy, pp. 602-606 - September
2001
Abstract : The paper presents a new and statistically robust algorithm
able to improve the performance of the standard DCT compression algorithm
for both perceived quality and compression size. The approach proposed
combines together an information theoretical/statistical approach with HVS
(human visual system) response functions. The methodology applied permits
us to obtain a suitable quantization table for specific classes of images
and specific viewing conditions. The paper presents a case study where the
right parameters are learned after an extensive experimental phase, for
three specific classes: document, landscape and portrait. The results show
both perceptive and measured (in term of PSNR) improvement. A further
application shows how it is possible obtain significant improvement
profiling the relative DCT error inside the pipeline of images acquired by
typical digital sensors.
[3]
A. Bosco - "Adaptive Image Denoising On Bayer
Pattern" - ST Journal of System Research. Vol.2, No.2, Dec.2001
[4]
A. Bosco, S. Battiato, M. Mancuso, G. Spampinato - "Temporal Noise Reduction of
Bayer Matrixed Data" - In Proceedings of IEEE ICME'02 (International Conference on Multimedia and Expo 2002) - Lausanne, Switzerland, August 2002
Abstract : This paper describes a new approach for noise reduction of
video sequences that directly processes raw data frames acquired by an
image sensor. The proposed noise reduction filter operates on Bayer
matrixed video sequences instead of the canonical YUV format allowing
saving of resources in terms of time and space; this is particularly
relevant for real time processing. Noise level is constantly monitored in
order to change the filter strength adaptively. Experiments show the
effectiveness of the proposed approach.
[5] A.Bosco, S. Battiato, M. Mancuso, G. Spampinato - "Adaptive Temporal Filtering for CFA
Video Sequences" - In Proceedings of IEEE ACIVS 2002 (Advanced Concepts for Intelligent Vision Systems) - Ghent University, Belgium, September
2002 (pdf
download)
Abstract : This paper describes a new approach for video sequences
noise reduction that directly processes raw data frames acquired by an
image sensor. The proposed noise reduction filter works on CFA (Color
Filter Array) Bayer matrixed video data instead of the canonical YUV
format. Working on CFA raw frames allows saving resources in terms of time
and space; this is particularly relevant for real time processing. Noise
level is continuosly monitored in order to modify the filter strength
adaptively. Experiments demonstrate the effectiveness of the proposed
method.
[6] G. Messina, A. Castorina,
S. Battiato, A. Bosco - "Automatic Global Image Enhancement by Skin
Dependent Exposure Correction" - in Proceedings of IEEE NSIP 2003
(Workshop on Nonlinear Signal and Image Processing) - Grado (Trieste),
Italy, June 2003 (pdf
download)
Abstract : The proposed method describes an automatic exposure correction
algorithm improved by a skin recognition technique. The approach analyzes
the Bayer data, captured using a ccd/cmos sensor, or the corresponding
color generated picture; after identifying the skin key features, the
algorithm adjusts the exposure level using a "camera response"-like
function. This method aims to solve some of the typical drawbacks featured
by handset devices (e.g. mobile phones) where several factors contribute
to acquire bad-exposed pictures: poor optics, absence of flashgun, etc.
[7]
A.
Bosco, S. Battiato, A. Castorina, K. Findlater - "A Temporal Noise
Reduction Filter Based on Full-Frame Data Image Sensors" - in
Proceedings of IEEE - ICCE 2003 (International Conference on Consumer
Electronics) - Los Angeles, June 2003 (pdf
download)
Abstract : This paper describes a temporal filter aimed at the
simultaneous cancellation of fixed pattern noise and temporal noise from
image sequences by exploiting all the data provided by a typical image
sensor (e.g. CCD/CMOS).
[8] G. Messina, A. Bosco,
S. Battiato, A. Castorina "Image Quality Improvement by
Adaptive Exposure Correction Techniques" - Proceedings of IEEE ICME03 International Conference on Multimedia and
Expo 2003 Baltimore USA July 2003 (pdf
download)
Abstract : The proposed paper concerns the processing of images in
digital format and, more specifically, particular techniques that can be
advantageously used in digital still cameras for improving the quality of
images acquired with non-optimal exposure. The proposed approach analyzes
the CCD/CMOS sensor Bayer data or the corresponding color generated image
and, after identifying specific features, it adjusts the exposure level
according to a "camera response" like function.
[9]
A. Bosco, K. Findlater,
S. Battiato, A. Castorina
" A Noise Reduction
Filter for Full-Frame Imaging Devices"
IEEE
Transactions on Consumer Electronics Vol. 49, Issue 3, August 2003
Abstract : This paper describes a method for video sequences denoising
that exploits extra-information provided by the image sensor. Fixed
Pattern Noise and Temporal Noise are removed by analyzing a series of
lines placed at the top of the imager.
[10]
G. Messina, A. Castorina,
S. Battiato, A. Bosco
"Improving
Digital Images by Adaptive Exposure"
Electronic Engineering Times ASIA
February 2004 (pdf
download) (Korean
version)
[11]
S. Battiato, A. Bosco, A. Castorina, G. Messina -
"Automatic
Image Enhancement by Content Dependent Exposure Correction"
EURASIP
Journal on Applied Signal Processing - 2004
[12]
A. Bosco, A. Bruna, G. Santoro,
P. Vivirito "Joint
Gaussian Noise Reduction and Defects Correction in RAW Digital Images"
IEEE NORSIG 2004 (6th Nordic Signal Processing Symposium)
Finland - June 2004
[13]
I. Guarneri, M. Guarnera, A. Bosco,
F. Vella "A
Quality Assessment Metric Based on Perceptual HVS Behaviors" IEEE ACIVS 2004 (Advanced
Concepts for Intelligent Vision Systems) Brussels, Belgium, Aug.31 - Sept
3, 2004
[14]
A. Bosco, A. Bruna, G. Messina, G. Spampinato "Fast Method for
Noise Level Estimation and Denoising" IEEE ICCE 2005 (International
Conference on Consumer Electronics) Las Vegas, January 2005
[15]
I. Guarneri, M. Guarnera, A. Bosco, G. Santoro
"Perceptual quality
metric for color interpolated images" SPIE Electronic Imaging 2005
January 2005
[16]
A. Bosco, A. Bruna, G. Messina, G. Spampinato "Fast Method For
Noise Level Estimation And Integrated Noise Reduction" IEEE
Transactions on Consumer Electronics, Vol. 51 Issue 3
August 2005
[17]
A. Bosco, A. Bruna, A. Capra, I. Guarneri "Spatio-Temporal
Filter With Adaptive Multiple Outliers Rejecter" IEEE ICCE 2006
(International Conference on Consumer Electronics) Las Vegas, January 2006
[18]
A. Bosco, A. Bruna, S. Smith, V. Tomaselli "Fast Noise Level
Estimation Using a Convergent Multiframe Approach" IEEE ICIP 2006
(International Conference on Image Processing) Atlanta, Georgia, USA,
October 2006
[19]
A. Bosco, A. Bruna, S. Battiato, G. Bella "Video Stabilization
through Dynamic Analysis of Frame Signatures" IEEE ICCE 2007
(International Conference on Consumer Electronics) Las Vegas, January 2007
Please
note: All papers listed above are subject to copyright limitations. Download
is allowed for personal use only.
Patents
(Brevetti):
[1] A. Bosco, M. Mancuso, "Noise Filter For Bayer Pattern Image Data" - No.01830562.3
-
European and U.S. Patent , March 2003.
[2] A. Bosco, S. Battiato, "Temporal Noise Reduction on CFA Video Sequences"
- European Patent pending, June 2002
[3] K. Findlater, A.Bosco, "Method
and apparatus for removing column fixed pattern noise in solid state image
sensors", Patent EP1475957
[4] A. Bosco, A. Bruna, "Noise
Filtering of Digital Images", 2004
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