USOORE42148E

(19) United States (12) Reissued Patent

(10) Patent Number: US RE42,148 E (45) Date of Reissued Patent: Feb. 15, 2011

Sheraizin et a]. (54)

METHOD AND APPARATUS FOR VISUAL

(56)

References Cited

LOSSLESS IMAGE SYNTACTIC ENCODING

(76)

Us PATENT DOCUMENTS

Inventors: Semion Sheraizin, 28B Harnagen Street, MaZkeret Batya 78604 (IL); Vitaly

2,697,758 A

8/1950 Little, Jr, .

Sheraizin, 28B Harnagen Street,

(commued)

MaZkeret Batya 78604 (IL)

FOREIGN PATENT DOCUMENTS EP

(21)

(22) Flled:

(Continued)

Aug“ 21’ 2008

OTHER PUBLICATIONS

Related US. Patent Documents

(64) Patent No.: Issued: App1_ NO;

“Notice ofAllowance”, U.S. Appl. No. 12/316,168, (Jun. 1, 2010), 9 pages

7,095,903 Aug. 22, 2006 11 /036,062 Jan. 18, 2005

Filed:

A visual perception threshold unit for image processing identi?es a plurality of visual perception threshold levels to be associated W1th the pixels of a Vldeo frame, wherein the

’

’

'

threshold levels de?ne contrast levels above Which a human

Foreign Application Priority Data

Jan. 23, 2000

eye can distinguish a pixel from among its neighboring pix els of the video frame. The present invention also includes a method of generating Visual perception thresholds by ana1y_

(IL) .............................................. .. 134182

Int_ CL G06K 9/38

sis of the details of the video frames, estimating the param eters of the details, and de?ning a visual perception thresh old for each detail in accordance With the estimated detail parameters. The present invention further includes a method

(200601)

U 5 Cl _' '

(58)

Primary ExamineriPhuoc Tran (57) ABSTRACT

15, 2002, now Pat N°~ 6,952,500, WhiCh is a continuation 0f application No. 09/524,618, ?led on Mar. 14, 2000, now Pat. NO 6 473 532 '

(52)

(Continued)

Continuation of application No. 10/121,685, ?led on Apr.

(30) (51)

9/1992

_

Reissue of:

(63)

0502615

Appl. No.: 12/196,180

382/270 382/263 ' """

""" """"""""""" "

’

of describing images by determining Which details in the

Field 0fClass1?cat10n Search ............ 382/162, 382/263’ 264’ 270’ 375/240'29

image can be distinguished by the human eye and which ones can only be detected by it.

See application ?le for complete search history.

Y'C ch

INPUT

'

FRAME

31 Claims, 15 Drawing Sheets

4O d

44 P ----- - ~1-- A

MEMORY

l

CURRENT

FRAME

PROCESSED

} 1 : CONTROLLABLE : FILTER BANK 60"? l

PREVIOUS

FRAME

'

621’“ {

l

FILTER SELECTOR

CURRENT FRAME 48

l

‘

i :

( PREVIOUS FRAME PROCESSOR

1 _________ __1 l

1

SPATIAL-

I 50

:

TEMPORAL

'L ______________________ __

Il ANALYZER DIFFEEENCE FILTERED FRAMES RAME

1 SUBCLASS @555 DETERMINER :

i

I

n

' l l : |

|

VISUAL THO PARAMETER PARAMETERS PERCEPTION i ESTIMATOR THRESHOLD DETERMINER

: I 1 | 1

INTER—

/

46

-ERAML. OUTPUT Y e c

FRAME '—"b> MEMORY

US RE42,148 E Page 2

US. PATENT DOCUMENTS

6,259,489 B1

7/2001 Flannaghan et al.

3,961,133 A

6/1976 Bennett

25233: E $2881 gew?k etal'

4,855,825 A

8/1989 Haikonen et a1.

6366 705 B1

4,947,255 A

8/1990 Jackson etal.

5,012,333 A 5,126,847 A 5,194,943 A

4/1991 Lee 6/1992 Kori 3/1993 Tomita etal.

5,245,445 5,301,016 5,339,171 5,341,442 5,384,601 5,404,174 5,428,398 5,467,404 5,488,675 5,491,514 5,491,517 5,491,519 5,510,824 5,537,510 5,539,475 5,542,008 5,555,557 5,557,340 5,565,921 5,566,251

A A A A A A A A A A A A A A A A A A A A

5,586,200 A 5,592,226 A 5,613,035 A 5,614,937 A

5,627,580 5,627,937 5,648,801 5,653,234 5,694,492 5,717,463 5,774,593 5,787,203 5,790,195 5,796,864 5,799,111 5,828,776 5,838,835 5,844,607 5,844,614 5,845,012 5,847,766 5,847,772

A A A A A A A A A A A A A A A A A A

.

9/1993 4/1994 8/1994 8/1994 1/1995 4/1995 6/1995 11/1995 1/1996 2/1996 2/1996 2/1996 4/1996 7/1996 7/1996 7/1996 9/1996 9/1996 10/1996 10/1996

12/1996 Devaneyetal.

5/1997 5/1997 7/1997 8/1997 12/1997 2/1998 6/1998 7/1998 8/1998 8/1998 8/1998 10/1998 11/1998 12/1998 12/1998 12/1998 12/1998 12/1998

Nelson Kim Beardsley et al. Kim et 31, Kim Brailean et al. Zick Lee et 31, Ohsawa Callahan Guissin Lee et 31, Martens Gebleretal. Chong etal, Jung Peak Wells

5,881,174 5,883,983 5,901,178 5,914,748 5,974,159 5,982,926 5,991,464 5,995,656

3/1999 3/1999 5/1999 6/1999 10/1999 11/1999 11/1999 11/1999

Kim Lee et 31, Lee et 31, Pamlski Lubin et 31, K110 et 31, ng et 31, Kim

6,005,626 A

12/1999 Dwg

6,014,172 6,037,986 6,055,340 6,094,511 6,097,848 6,100,625 6,130,723 6,191,772 6,229,925 6,236,751

1/2000 3/2000 4/2000 7/2000 8/2000 8/2000 10/2000 2/2001 5/2001 5/2001

Niesen Gouliardon et al. Nagao Metcalfe et al. Salvati Yamamoto Medin Mical et al. Alexandre et al. Farrell

,

oshidome

4/2002 Ch.

’

t 1

.‘u.e 3'

6,385,647 B1 6,404,460 B1 6,463,173 B1

5/2002 WllllS et al. 6/2002 Chen et al. 10/2002 Tram

6,466,912 6,473,532 6,509,158 6,522,425 6,554,181 6,559,826 6,567,116 6,580,825 6,610,256 6,628,327 6,643,398 6,707,487 6,728,317 6,753,929 6,757,449 6,782,287 6,835,693 6,845,181 6,847,391 6,873,442

10/2002 10/2002 1/2003 2/2003

6,940,545

1/1997 Lee et 31, 3/1997 Kim 3/1997 Nelson

12/1998 Apostolopoulosetal. 12/1998 Gupta et 31, 2/1999 Kim

A A A A A A A B1 B1 B1

’

Fujisawa Gehrmann Fujisawa Barrett Yamashitaet 31, Sugahara Faroudja Vuylsteke Hanna Fukuda Kreitman et 31, Kim Nelson Kim Sadjadian et al. Sugahara et 31, Mailloux Millward Sasakiet al. Hanna et 31,

5,850,294 A 5,852,475 A 5,870,501 A A A A A A A A A

,

6,940,903 6,970,506 7,003,174

7,049,074 7,075,993 7,087,021 7,110,601 7,133,451 7,139,425 7,164,717 7,184,071 7,221,706 7,221,805 7,526,142 7,639,892 7,742,108 2001/0003545 2002/0015508 2002/0104854 2002/0122494 2002/0181598

2003/0107681 2003/0122969 2003/0152283 2004/0091145 2004/0184673 2004/0190789 2005/0013485 2005/0259185 2006/0013503 2009/0161754

B1 B1 B1 B2 B1 B1 B1 B2 B2 B1 B2 B1 B1 B1 B1 B2 B2 B2 B1 B1 B1 B2 B2 B2 B2 B2 B2 B2 B2 B2 B2 B2 B2 B1 B2 B2 B2 A1 A1 A1 A1 A1 A1 A1 A1 A1 A1 A1 A1 A1 A1 A1

JOhIIStOIl SheraiZin SchwaItZZ Yoshidome

4/2003 Dammers et al. 5/2003 Mendelson et al. 5/2003 Aman et al.

6/2003 BhaSkar 8/2003 Schwartz 9/2003 11/2003 3/2004 4/2004 6/2004 6/2004 8/2004 12/2004 1/2005 1/2005 3/2005

Aoki et al. Moriwaki Aman DemOS SheraiZin L006 Grzeszczuk Bourdelais et al. Dupin et al. Kassatly Gindele et al.

9/2005 Ray etal~ 9/2005 Zhao et al. 11/2005 Kim et al. 2/2006 Kryukov et al.

5/2006 7/2006 55/2006 9/2006 11/2006 11/2006 1/2007 2/2007 5/2007 5/2007 4/2009 12/2009 6/2010 6/2001 2/2002 8/2002 9/2002 12/2002

Schwartz O’Brien Paternostro Yanagisawa Kim et al. Takahashi Katsavounidis Chellappa et al. Zhao et al. Bachelder SheraiZin et al. SheraiZin SheraiZin et al. H9118 Hannigan et al. Lan SheraiZin Vetro et al.

6/2003 MasayukietaL 7/2003 Higuchi 8/2003 Kagumi 5/2004 9/2004 9/2004 1/2005 11/2005 1/2006 6/2009

Kohashi Watanabe Liu et al. Masaki Kim et al. Kim SheraiZin et al.

FOREIGN PATENT DOCUMENTS EP

0729117

8/1996

GB

1503612

3/1978

JP JP JP JP JP WO

55-71363 6-133221 01206775 4-83480 08-191440 W000/19726

5/1980 7/1985 8/1989 3/1992 7/1996 4/2000

US RE42,148 E Page 3

Chang, Dah£hung “Image contrast enhancement based on

OTHER PUBLICATIONS

“Non Final O?ice Action”, U.S. Appl. No. 10/898,557, (Jun. 8,2010), 5 pages. “Notice ofAllowability”, U.S. Appl. No. 12/316,168, (Jun. 29, 2010), 7 pages. “Non Final O?ice Action”, U.S. Appl. No. 12/316,168, (Jun. 24, 2009), 11 pages. “Non Final O?ice Action”, U.S. Appl. No. 10/898,557, (Jul. 8, 2009), 6 pages.

local standard deviation”, IEEE trans on medical imaging,

vol. 17, No. 4,(Aug. 1998), 5184531. Kim, Yeong T., “Contrast enhancement using brightness pre serving biihistogram equalization”, IEEE trans on con

sumer electronics, vol. 43, No. 1,(Feb. 1997),1*8. Kim, Tae K., et al., “Contrast enhancement system using

spatiallly adaptive histogram equalization With temporal ?l tering”, IEEE trans on consumer electronics, vol. 44, No.

“Notice of Allowance/Base Issue Fee”, U.S. Appl. No.

1,(Feb. 1998),82*87.

11/027,674, (Jul. 23, 2009), 6 pages. “Notice ofAllowance”, U.S. Appl. No. 11/027,674, (Feb. 24,

Sakaue, Shigeo et al., “Adaptive gamma processing of the video camera for expansion of the dynamic range”, IEEE

2009), 16 pages. “Restriction Requirement”, U.S. Appl. No. 10/851,190,

trans on consumer electronics, vol. 41, No. 3,(Aug. 1995), 5554582.

(May 19, 2009),8 pages. “Notice ofAllowance”, U.S. Appl. No. 10/898,557, (Jan. 27,

Russ, John C., “The image processing handbook”, CRS press Inc., (1995),674. Talluri, Raj et al., “A Robust, Scalable, ObjectiBased Video Compression Technique for Very LoW BitiRate Coding”, IEEE Transaction of Circuit and Systems for Video Technol ogy, (Feb. 1997),vol. 7, No. 1. Awadkh, AliAsmari “An Adaptive Hybrid Coding Scheme

2010), 6 pages.

“Notice ofAllowance”, U.S. Appl. No. 12/316,168, (Jan. 29, 2010), 8 pages.

“Notice ofAllowance”, U.S. Appl. No. 10/851,190, (Feb. 8, 2010), 4 pages. “Non Final Of?ce Action”, U.S. Appl. No. 10/851,190, (Sep. 1, 2009), 8 pages.

Banhom, et al., “Digital Image Restoration”, IEEE Signal

Proc., (Mar. 1997),2441. BelkacemiBoussaid, “A NeW Image Smoothing Method Based on a Simple Model of Spatial Processing in the Earl Stages of Human Vision”, IEEE Trans. on Image Proc., vol.

9, No. 2,(Feb. 2000),220*226. Chan, “A practical postprocessing technique for realitime

for HDTV and Digital Sequences”, IEEE Transacitons on

Consumer Electronics, vol. 42, No. 3,(Aug. 1995),926*936. Kwok, Tung Lo “Predictive Mean Search Algorithms for Fast VQ Encoding of Images”, IEEE Transactions On Con sumer Electronics, vol. 41, No. 2,(May 1995),327*331. Goel, James et al., “Preiprocessing for MPEG Compression

Using Adaptive Spatial Filtering”, IEEE Transactions On

blockibased coding sytem”, IEEE trans on circuits and sys

Consumer electronics, vol. 41, No. 3,(Aug. 1995),687*698. Feng, Jian et al., “Motion Adaptive Classi?ed Vector Quan

temsfor video technology, vol. 8, No. 1(Feb. 1998),4*8.

tization for ATM Video Coding”, IEEE Transactions on

Liu, et al., “A neW postprocessing technique for the block based DCT coding based on the convexi projection theory”,

Consumer Electronics,, vol. 41, No. 2,(May 1995),322*326. Lan, Austin Y., et al., “SceneiContext Dependent Refer

IEEE trans on consumer electronics, vol. 4, No. 3,(Aug.

enceiFrame Placement for MPEG Video Coding”, IEEE Transactions on Circuits and Systems for Video Technology,

1998), 105441061. Lee, et al., “Ef?cient algorithm and architecture for post processor in HDTV”, IEEE trans on consumer electronics,

vol. 9, No. 3,(Apr. 1999),478489. Fan, KuoiChin et al., “An Active Scene AnalysisiBased approach for Pseudo constant BitiRate Video Coding”,

vol. 44, No. 1,(Feb. 1998), 16426. Choung, et al., “A fast adaptive image restoration ?lter for reducing block artifact in compressed images”, IEEE trans

IEEE Transactions on Circuits and Systems for Video Tech

on

Takashi, Ida et al., “Image Segmentation and Contour Detec

consumer

electronics,

vol.

44,

No.

1,(Nov.

nology, vol. 8, No. 2,(Apr. 1998),159*170.

1997),1340*1346.

tion Using Fractal Coding”, IEEE Transitions on Circuits

Jeon, B et al., “Blocking artifacts reduction in image com

and Systemsfor Video Technology, vol. 8, No. 8,(Dec. 1998),

pression With block boundary discontinuity criterion”, IEEE trans on circuits and systems for video technology, vol. 8,

No. 3,(Jun. 1998),34557. Zhong, et al., “Derivation of prediction equation for block ing effect reduction”, IEEE trans on circuits and systems for

video technology, vol. 9, No. 3,(Apr. 1999),415*418. Meier, et al., “Reduction of blocking artifacts in image and video coding”, IEEE trans on cicuits and systems for video

technology, (Apr. 1999),490*500. Kim, et al., “An advanced contrast enhancement using par

tially overlapped subiblock histogram equalization”, IEEE Trans on circuits and systemsfor video technology, vol. 11,

No. 4,(Apr. 2001),475484.

9684975.

Liang, Shen “A SegmentationiBased Lossless Image Cod ing Method for HighiResolution Medical Image Compres sion”, IEEE Transactions on Medical Imaging, vol. 16, No.

3,(Jun. 1997),301*316. Munteanu, Adrian et al., “WaveletiBased Lossless Com

pression of Coronary Angiographic Images”, IEEE Transac tions

on Medical Imaging,

vol.

18,

No.

3,(Mar.

1999),272*281. Okumura, Akira et al., “Signal Analysis and Compression performance Evaluation of Pathological Microscopic Images”, IEEE Transactions on Medical Imaging, vol. 16,

Stark, Alex J ., “Adaptive image contrast enhancement

No. 6,(Dec. 1997),701*710.

Enhancement using generalizations of histogram equaliza

Pappas, et al., “Digital Color Restoration of Old Paintings”, IEEEE Trans. on Image Proc., vol. 9, No. 2,(Feb. 2000),

tion”, IEEE trans on image processing, vol. 9, No. 5,(May

2000),889*896.

2914294.

Hier, et al., “Real time locally adaptive contrast enhance ment; A practical key to overcoming display and human

toning”, IEEE Trans. on Image Proc., vol. 11, No. 3,(Mar.

visual system limitation”, SID digest, (1993),4914193.

2002),258*269.

Kim, et al., “Impact of HVS Models on Modelibased Half

US RE42,148 E Page 4

Hentschel, et al., “Effective Paking Filter and is Implemen tation on a Programmable Architecture”, IEEE Trans. on

Consumer Electronics, vol. 47, No. 1,(Feb. 2001),33*39. Yang, et al., “MaximumiLikelihood Parameter Estimation for Image RingingiArtifact Removal”, IEEE Trans. on

Cicuits and Systems for Video Technology, vol. 11, No.

8,(Aug. 2001),9634973. Immerkaer, “Use of Blur*Space of Deblurring and Edgei Preserving Noise Smoothing”, IEEE Trans On Image Proc., vol. 10, No. 6,(Jun. 2001),8374840. Chan, et al., “The Digital TV Filter and Nonlinear Denois ing”, IEEE Trans on Image Proc., vol. 10, No. 2,(Feb. 2001), 23 14241 .

Liu, et al., “Complexityi Regularized Image Denoising”, IEEE Trans on Image Processing, vol. 10, No. 6,(Jun. 2001),

Polesel, Andrea et al., “Image Enhancement Via Adaptive Unsharp Masking”, IEEE transactions on image processing,

vol. 9, No. 3,(Mar. 2000),505*510. Olukayode, A et al., “An algorithm for integrated noise reduction and sharpness enhancement”, IEEE Transactions on Consumer Electronics, vol. 46, No. 3,(Aug.

2000),4744180. SungiHoon, Hong, “Joint video coding of MPEG42 video programs for digital broadcasting services”, IEEE transac tions on broadcasting, vol. 44, No. 2,(.Iun. 1998),153*164. Lim, Jae “Two dimensional signal and image processing”, USA Simon & Schuster, (1990),430. Sherazain, et al., “US. Appl. No. 09/524,618”, ?led Mar. 14,

3414351.

2000.

Jostschulte, et al., “Perception Adaptive Temporal TVinoise Reduction Using Contour Preserving Pre?lter Techniques”,

Leonard, Eugene “Considerations regarding the use of digi tal data to generate video backgrounds”, SMPTE journal,

IEEE on Consumer Electronics, vol. 44, No. 3,(Aug. 1998),

vol. 87,,(Aug. 1987),4994504.

109141096.

Brice, Richard “Multimedia and Virtual Reality Engineer

ing”, (1997),1*8, 1744175, 2804283. Conway, Lynn et al., “Video mirroring and Iconic Gestures: Enhancing Basic Videophones to Provide Visual Coaching

Tescher, AndreW “Multimedia is the message”, IEEE signal

processing magazine, vol. 16, No. 1,(.Ian. 1999),44*54. Mancuso, et al., “A neW postiprocessing algorithm to reduce artifacts in block coded images”, IEEE trans on consumer

and Visual Control”, IEEE Transactions on Consumer Elec

electronics, vol. 43, No. 3,(Aug. 1997),303*307.

tronics, vol. 44, No. 2,(May 1998),3884397. Cheol, Hong M., et al., “A neW adaptive quantization

Yang, J et al., “Noise estimation for blocking artifacts reduc tion in DCT coded images”, IEEE trans on circuits and sys

method to reduce blocking effect”, IEEE transaction on con

tems for video tech nology, vol. 10, No. 7,(Oct.

sumer electronics, vol. 44, No. 3,(Aug. 1998),768*772. Massimo, Mancuso et al., “Advanced pre/ post processing

2000),1116*1120.

for DCT coded images”, IEEE transactions on consumer

electronics, vol. 44, No. 3,(Aug. 1998),1039*1041. Tao, Chen “Adaptive post?ltering of transform coef?cients

Kuo, et al., “Adaptive postprocessor for block endoded images”, IEEE trans on circuits and systems for video tech

nology, vol. 5, No. 4,(Aug. 1995),298*304.

for the reduction of blocking artifacts”, IEEE transactions on circuits and systems for video technology, vol. 11, No.

blocking effect”, IEEE Trans on consumer electronics, vol.

5,(May 2001),5944602.

44, No. 3,(Aug. 1998),7684772.

Min, et al., “A neW adaptive quantization method to reduce

U S. Patent

Feb. 15, 2011

Sheet 1 0f 15

US RE42,148 E

US. Patent

Feb. 15, 2011

US RE42,148 E

Sheet 4 0f 15

szm

lmOI em r PQIw

NIE¢ NIzm NIEN

0W00

mm! ma:

: md

m6

Q0

in

NIEP

US. Patent

Feb. 15, 2011

_ _

|ll\_ ilI_r Flilll

n “and;moflsml _ _ _ .n m m

_ _

_ _ _ _

“n"E1Q85}1;%. n u p”; Q

US RE42,148 E

Sheet 5 0f 15

FH“$6S1i“5%m: _m u + 2 S 1 . i l % 5 n a : 1 m '30. u " “ I42

_i.j|l

i“ Q i 8* m 1| ++19:2 S QIEZ 5

E»


US. Patent

Feb. 15, 2011

US RE42,148 E

Sheet 6 0f 15

_‘

I I I I l I I I

K4: IlII|_ F

aH91m1i%5|.:szmi:E

l I l I

m. “ n NE 5 _ _

u n:16E$15Il1.eé w " 2: NE

_ _

? _

n$215-21%sz

_ _

_ _

m 221%+.151 '— i m w I +i 52 m

I I I I |

I I

I l I I I I I I l

FQImJ

Nolmd

US. Patent

Feb. 15, 2011

US RE42,148 E

Sheet 7 0f 15

NIzm i1l."

/ /

///i o;

md

/

wd

/

m6

// /

.30

QUE

MiEnm/:nj / {/10%15/ £5N135

/K115 PmO O

y A.

nd

N6

70

US. Patent

Feb. 15, 2011

Sheet 8 0f 15

US RE42,148 E

1.6 1.4 1.2 1.0

/

Vout THDl

8 1

6 1

1.4

2 1

0 1

(l8

FIG?

6 0

0.4 0.2

02040608

US. Patent

Feb. 15, 2011

US RE42,148 E

Sheet 9 0f 15

8/

50? mm

)i8?

E.\2\ Ln:5

\

a519:

KIgm 55 *

m4ogézo

105628

E/

mm _

om

@56

US. Patent

Feb. 15, 2011

US RE42,148 E

Sheet 10 0f 15

1502.»

m¢/I

a

mm

2\ME\E”:

Ln:gm

*5 5

ME S

I/iQaw

&1gm

.9:

105$on

\

89>me H3¢z_ .cm wQOE Pzwmao m2
mwdE

US. Patent

Feb. 15, 2011

502»A.

EO :

H

US RE42,148 E

Sheet 11 0f 15

1/®¢

8/

mm

1

E

\

DEgm

*51$:

k:5 55_

10258

11mmi)98

61+“21&5on

wam o zm o m§
2m65»%:

owdE

US. Patent

Feb. 15, 2011

Sheet 12 0f 15

a2mi.12n_s_

a:m2a2n3

I|._r
US RE42,148 E

US. Patent

Feb. 15, 2011

5,

v?mlo:ul

US RE42,148 E

Sheet 13 0f 15

\> .

>£HI

a.oS'uElI lHmEJwoIasl;

a:i

“-3"2m1a. u%Nl wH5|.Eo_+u“lin J1

\\ Q> E +

.5

E»

US. Patent

Feb. 15, 2011

Sheet 14 0f 15

US RE42,148 E

P')

"E"

:11

*

‘

LO

HPF—A MF

FIG.1OB MF

US RE42,148 E 1

2 Jian Feng et a1. “Motion Adaptive Classi?ed Vector Quan

METHOD AND APPARATUS FOR VISUAL LOSSLESS IMAGE SYNTACTIC ENCODING

tization for ATM Video Coding”, IEEE Transactions on

Consumer Electronics, vol. 41, No. 2, p. 3224326, May

1995;

Matter enclosed in heavy brackets [ ] appears in the original patent but forms no part of this reissue speci?ca

Austin Y. Lan et al., “Scene-Context Dependent ReferenceiFrame Placement for MPEG Video Coding,”

tion; matter printed in italics indicates the additions made by reissue.

IEEE Transactions on Circuits and Systems for Video

Technology, vol. 9, No.3, pp. 4784489, April 1999; CROSS-REFERENCE TO RELATED APPLICATIONS

Kuo-Chin Fan, Kou-Sou Kan, “An Active Scene Analysis Based approach for Pseudoconstant Bit-Rate Video Coding”, IEEE Transactions on Circuits and Systems for

This application is a continuation application of US. Ser. No. 10/121,685, ?led Apr. 15, 2002, now US. Pat. No. 6,952,500, Which is a continuation application of US. Ser. No. 09/524,618, ?led Mar. 14, 2000, issued as US. Pat. No. 6,473,532, Which patents are incorporated herein by refer

Video Technology, vol. 8 No.2, pp. 1594170, April 1998; Takashi Ida and Yoko Sambansugi, “Image Segmentation and Contour Detection Using Fractal Coding”, IEEE Trans actions on Circuits and Systems for Video Technology, vol.

8, No. 8, pp. 9684975, December 1998; Liang Shen and Rangaraj M. Rangayyan, “A Segmentation-Based Lossless Image Coding Method for

ence.

FIELD OF THE INVENTION

The present invention relates generally to processing of

20

High-Resolution Medical Image Compression,” IEEE Transactions on Medical Imaging, vol. 16, No. 3, pp.

video images and, in particular, to syntactic encoding of images for later compression by standard compression tech

3014316, June 1997;

niques.

Adrian Munteanu et al., “Wavelet-Based Lossless Com

pression of Coronary Angiographic Images”, IEEE Transac BACKGROUND OF THE INVENTION

25

tions on Medical Imaging, vol. 18, No. 3, p. 2724281, March

30

1999; and Akira Okumura et al., “Signal Analysis and Compression Performance Evaluation of Pathological Microscopic Images,” IEEE Transactions on Medical Imaging, vol. 16, No. 6, pp. 7014710, December 1997.

There are many types of video signals, such as digital

broadcast television (TV), video conferencing, interactive TV, etc. All of these signals, in their digital form, are divided into frames, each of Which consists of many pixels (image elements), each of Which requires 8424 bits to describe them. The result is megabits of data per frame.

SUMMARY OF THE INVENTION

Before storing and/or transmitting these signals, they typi

An object of the present invention is to provide a method

cally are compressed, using one of many standard video

compression techniques, such as JPEG, MPEG,

and apparatus for video compression Which is generally 35

H-compression, etc. These compression standards use video

signal transforms and intra- and inter-frame coding Which exploit spatial and temporal correlations among pixels of a frame and across frames.

However, these compression techniques create a number

40

of well-known, undesirable and unacceptable artifacts, such

threshold levels de?ne contrast levels above Which a human

as blockiness, low resolution and Wiggles, among others. These are particularly problematic for broadcast TV (satellite TV, cable TV, etc.) or for systems With very low bit

rates (video conferencing, videophone).

45

threshold unit Which includes a parameter generator and a

standard compression techniques. The following patents and articles discuss various prior art methods to do so:

US. Pat. Nos. 5,870,501, 5,847,766, 5,845,012, 5,796,

50

IEEE Transactions of Circuit and Systems for Video

trast levels above Which a human eye can distinguish a pixel 55

Scheme for HDTV and Digital Sequences,” IEEE Transac tions on Consumer Electronics, vol. 42, No. 3, pp. 9264936,

from among its neighboring pixels of the frame. Moreover, in accordance With a preferred embodiment of the present invention, the parameter generator includes a volume unit, a color unit, an intensity unit or some combina

August 1995; Kwok-tung Lo and Jian Feng, “Predictive Mean Search Algorithms for Fast VQ Encoding of Images,” IEEE Trans

threshold generator. The parameter generator generates a multiplicity of parameters that describe at least some of the information content of the processed frame. From the

parameters, the threshold generator generates a plurality of visual perception threshold levels to be associated With the pixels of the video frame. The threshold levels de?ne con

Raj Talluri et al, “A Robust, Scalable, Object-Based Video Compression Technique for Very Low Bit-Rate Coding,”

Technology, vol. 7, No. 1, February 1997; Awath. Al-Asmari, “An Adaptive Hybrid Coding

eye can distinguish a pixel from among its neighboring pix els of the video frame. There is also provided, in accordance With a preferred

embodiment of the present invention, the visual perception

Much research has been performed to try and improve the

864, 5,774,593, 5,586,200, 5,491,519, 5,341,442;

lossless vis-a-vis What the human eye perceives. There is therefore provided, in accordance With a pre ferred embodiment of the present invention, a visual percep tion threshold unit for image processing. The threshold unit identi?es a plurality of visual perception threshold levels to be associated With the pixels of a video frame, Wherein the

60

tion of the three. The volume unit determines the volume of information in the frame, the color unit determines the per pixel color and the intensity unit determines a cross-frame

actions On Consumer Electronics, vol. 41, No. 2, pp.

change of intensity.

3274331, May 1995;

There is also provided, in accordance With a preferred embodiment of the present invention, a method for generat

James Goel et a1. “Pre-processing for MPEG Compres

sion Using Adaptive Spatial Filtering”, IEEE Transactions On Consumer Electronics, vol. 41, No. 3, pp. 6874698,

August 1995;

65

ing visual perception thresholds. The method includes analysis of the details of the frames of a video signal, esti mating the parameters of the details, and de?ning a visual