Method and apparatus for reduction of image data compression noise
First Claim
1. A method for reducing the effects of blocking artifacts attributable to quantization incurred in the transform image coding and compression of a two-dimensional image signal into a digital image, the degree of compression determined by a scaling factor κ
- and a quantization table, and the image signal provided as a series of electrical signals, each electrical signal corresponding to a characteristic of an element of a two-dimensional image, where the image elements have been configured as a two-dimensional H×
V array, said method comprising the steps of;
converting the series of electrical signals into a set of numerical values, each said numerical value quantitatively describing a feature characteristic of a corresponding image element, said numerical values further denoted by s0 (z,y) where 0≦
y≦
H-1 and 0≦
z≦
V-1;
formatting said set of numerical values into a plurality of N×
N image data matrices identified by indices `p` and `q`, each said image-data matrix comprising image-data terms denoted by sq,p (j,i), each said image data term comprised of a said numerical value determined in accordance with the relationship;
space="preserve" listing-type="equation">s.sub.q,p (j,i)=s.sub.0 (j+Nq,i+Np)where 0≦
i,j≦
N-1;
transforming each said image-data matrix into an N×
N frequency-coefficient matrix comprising frequency-coefficient terms denoted by Sq,p (υ
,μ
), said step of transforming each said image-data matrix accomplished by means of an orthogonal transform basis matrix C in accordance with the expression,
space="preserve" listing-type="equation">S.sub.q,p (υ
,μ
)=C×
s.sub.q,p (j,i)×
C.sup.T ;
dividing each said frequency-coefficient term Sq,p (υ
,μ
) by a scaled quantization term denoted by Q(υ
,μ
), said scaled quantization term obtained from the quantization table and modified by the scaling factor, to yield a plurality of N×
N quotient-coefficient matrices comprising quotient terms denoted by Qu q,p (υ
,μ
) derived in accordance with the expression, ##EQU16## rounding each said quotient term to a less precise value to yield a quantized-coefficient matrix comprising quantized-quotient terms denoted by Qcq,p (υ
,μ
) in accordance with the expression, ##EQU17## subtracting each said quantized-coefficient term Qcq,p (υ
,μ
) from a corresponding said quotient term Quq,p (υ
,μ
) to form a plurality of N×
N difference-coefficient matrices comprising difference terms Dcq,p (υ
,μ
) derived in accordance with the expression, ##EQU18## deriving a quantization error matrix, comprising terms E0 (υ
,μ
), by summing and averaging error terms, said error terms comprising functions of said difference-coefficient matrices;
selecting a set of filter parameters, denoted by α and
β
;
multiplying each said quantized coefficient term by a corresponding quantization term to yield a plurality of N×
N mask-multiplied transform coefficient matrices comprising terms denoted by Rq,p (υ
,μ
) derived in accordance with the expression,
space="preserve" listing-type="equation">R.sub.q,p (υ
,μ
)=Qc.sub.q,p (υ
,μ
)×
Q(υ
,μ
);
applying an inverse orthogonal transform to said mask-multiplied transform coefficient matrices to yield a plurality of N×
N received image-data matrices denoted by rq,p (j,i), in accordance with the inverse transform equation,
space="preserve" listing-type="equation">r.sub.q,p (j,i)=C.sup.T ×
R.sub.q,p (υ
,μ
)×
C;
formatting said received image-data matrices into an H×
V received image-data set comprising terms denoted by sR (z,y), in accordance with the equation,
space="preserve" listing-type="equation">s.sub.R (j+Nq,i+Np)=r.sub.q,p (j,i)where 0≦
i+Np≦
H-1 and 0≦
j+Nq≦
V-1;
forming said received image data set into a plurality of N×
N overlapped image-data matrices comprising terms denoted by vs,r (j,i), in accordance with the equation,
space="preserve" listing-type="equation">v.sub.s,r (j,i)=s.sub.R (j+ω
s, i+ω
r);
transforming said overlapped image-data matrices into modified coefficient matrices comprising terms denoted by Svs,r (υ
,μ
), in accordance with the equation,
space="preserve" listing-type="equation">Sv.sub.s,r (υ
,μ
)=C×
v.sub.s,r (j,i)×
C.sup.T ;
converting said modified coefficient matrices into filtered coefficient matrices by means of said quantization error matrix and said filter parameters, said modified coefficient matrix comprising terms denoted by Sfs,r (υ
,μ
), said step of converting said modified coefficient matrices performed in accordance with the equation, ##EQU19## transforming said filtered coefficient matrices into filtered image-data matrices in accordance with the transform equation,
space="preserve" listing-type="equation">rf.sub.s,r (j,i)=C.sup.T ×
Sf.sub.s,r (υ
,μ
)×
C; and
converting said filtered image-data matrices into a series of filtered electrical signals such that said filtered electrical signals can be configured into a two-dimensional H×
V array of filtered image elements, each said filtered electrical signal corresponding to a characteristic of one said filtered image element.
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Abstract
An image encoding/decoding apparatus for performing transform coding by a method in which blocking artifacts are suppressed or eliminated is disclosed in which encoded data, transmitted by the encoding apparatus, is converted into received image data terms which are subsequently overlap transformed into frequency coefficients for modification by means of a filtering operation utilizing a quantization error matrix. The quantization error matrix can be derived from quantization error data generated in the encoding unit, or can be provided as a look-up table in the decoding unit. The modified frequency coefficients are converted into reduced-noise image data terms for reconstruction into a digital image.
192 Citations
52 Claims
-
1. A method for reducing the effects of blocking artifacts attributable to quantization incurred in the transform image coding and compression of a two-dimensional image signal into a digital image, the degree of compression determined by a scaling factor κ
- and a quantization table, and the image signal provided as a series of electrical signals, each electrical signal corresponding to a characteristic of an element of a two-dimensional image, where the image elements have been configured as a two-dimensional H×
V array, said method comprising the steps of;converting the series of electrical signals into a set of numerical values, each said numerical value quantitatively describing a feature characteristic of a corresponding image element, said numerical values further denoted by s0 (z,y) where 0≦
y≦
H-1 and 0≦
z≦
V-1;formatting said set of numerical values into a plurality of N×
N image data matrices identified by indices `p` and `q`, each said image-data matrix comprising image-data terms denoted by sq,p (j,i), each said image data term comprised of a said numerical value determined in accordance with the relationship;
space="preserve" listing-type="equation">s.sub.q,p (j,i)=s.sub.0 (j+Nq,i+Np)where 0≦
i,j≦
N-1;transforming each said image-data matrix into an N×
N frequency-coefficient matrix comprising frequency-coefficient terms denoted by Sq,p (υ
,μ
), said step of transforming each said image-data matrix accomplished by means of an orthogonal transform basis matrix C in accordance with the expression,
space="preserve" listing-type="equation">S.sub.q,p (υ
,μ
)=C×
s.sub.q,p (j,i)×
C.sup.T ;dividing each said frequency-coefficient term Sq,p (υ
,μ
) by a scaled quantization term denoted by Q(υ
,μ
), said scaled quantization term obtained from the quantization table and modified by the scaling factor, to yield a plurality of N×
N quotient-coefficient matrices comprising quotient terms denoted by Qu q,p (υ
,μ
) derived in accordance with the expression, ##EQU16## rounding each said quotient term to a less precise value to yield a quantized-coefficient matrix comprising quantized-quotient terms denoted by Qcq,p (υ
,μ
) in accordance with the expression, ##EQU17## subtracting each said quantized-coefficient term Qcq,p (υ
,μ
) from a corresponding said quotient term Quq,p (υ
,μ
) to form a plurality of N×
N difference-coefficient matrices comprising difference terms Dcq,p (υ
,μ
) derived in accordance with the expression, ##EQU18## deriving a quantization error matrix, comprising terms E0 (υ
,μ
), by summing and averaging error terms, said error terms comprising functions of said difference-coefficient matrices;selecting a set of filter parameters, denoted by α and
β
;multiplying each said quantized coefficient term by a corresponding quantization term to yield a plurality of N×
N mask-multiplied transform coefficient matrices comprising terms denoted by Rq,p (υ
,μ
) derived in accordance with the expression,
space="preserve" listing-type="equation">R.sub.q,p (υ
,μ
)=Qc.sub.q,p (υ
,μ
)×
Q(υ
,μ
);applying an inverse orthogonal transform to said mask-multiplied transform coefficient matrices to yield a plurality of N×
N received image-data matrices denoted by rq,p (j,i), in accordance with the inverse transform equation,
space="preserve" listing-type="equation">r.sub.q,p (j,i)=C.sup.T ×
R.sub.q,p (υ
,μ
)×
C;formatting said received image-data matrices into an H×
V received image-data set comprising terms denoted by sR (z,y), in accordance with the equation,
space="preserve" listing-type="equation">s.sub.R (j+Nq,i+Np)=r.sub.q,p (j,i)where 0≦
i+Np≦
H-1 and 0≦
j+Nq≦
V-1;forming said received image data set into a plurality of N×
N overlapped image-data matrices comprising terms denoted by vs,r (j,i), in accordance with the equation,
space="preserve" listing-type="equation">v.sub.s,r (j,i)=s.sub.R (j+ω
s, i+ω
r);transforming said overlapped image-data matrices into modified coefficient matrices comprising terms denoted by Svs,r (υ
,μ
), in accordance with the equation,
space="preserve" listing-type="equation">Sv.sub.s,r (υ
,μ
)=C×
v.sub.s,r (j,i)×
C.sup.T ;converting said modified coefficient matrices into filtered coefficient matrices by means of said quantization error matrix and said filter parameters, said modified coefficient matrix comprising terms denoted by Sfs,r (υ
,μ
), said step of converting said modified coefficient matrices performed in accordance with the equation, ##EQU19## transforming said filtered coefficient matrices into filtered image-data matrices in accordance with the transform equation,
space="preserve" listing-type="equation">rf.sub.s,r (j,i)=C.sup.T ×
Sf.sub.s,r (υ
,μ
)×
C; andconverting said filtered image-data matrices into a series of filtered electrical signals such that said filtered electrical signals can be configured into a two-dimensional H×
V array of filtered image elements, each said filtered electrical signal corresponding to a characteristic of one said filtered image element. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
- and a quantization table, and the image signal provided as a series of electrical signals, each electrical signal corresponding to a characteristic of an element of a two-dimensional image, where the image elements have been configured as a two-dimensional H×
-
9. A method for reducing the effects of blocking artifacts attributable to quantization incurred in the transform image coding and compression of a two-dimensional image signal into a digital image, the degree of compression determined by a scaling factor κ
- and a quantization table, and the image signal provided as a series of electrical signals, each electrical signal corresponding to a characteristic of an element of a two-dimensional image, where the image elements have been configured as a two-dimensional H×
V array, said method comprising the steps of;transform image coding the two-dimensional H×
V array of image elements to form a coded image-data set by means of an orthogonal transform basis matrix, said step of transform image coding comprising a quantization operation;decoding said coded image-data set by means of said orthogonal transform basis matrix to form a decoded image-data set; converting said decoded image-data set into a plurality of frequency coefficient terms by means of said orthogonal transform basis matrix; filtering said plurality of frequency coefficient terms by means of a filtering computation, said filtering computation comprising the step of multiplying said frequency coefficient terms with a coefficient filtering term to form a plurality of filtered frequency coefficient terms; and converting said filtered frequency coefficients into a reduced-noise digital image. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16, 17)
- and a quantization table, and the image signal provided as a series of electrical signals, each electrical signal corresponding to a characteristic of an element of a two-dimensional image, where the image elements have been configured as a two-dimensional H×
-
18. A method for filtering a two-dimensional decoded image signal such that the effects of blocking artifacts attributable to quantization are reduced, the blocking artifacts arising in the decoded image signal as a consequence of there having been performed transform image coding, data compression, and quantization on an antecedent image signal, the antecedent image signal having been provided as a series of electrical signals, each electrical signal corresponding to a characteristic of an element of the antecedent image, where the compression operation utilized a scaling factor κ
- and quantization terms derived from a quantization table, and where the decoded image signal has been configured as a two-dimensional H×
V set of image-data terms denoted by SR (z,y), said method comprising the steps of;defining an overlap parameter, denoted by ω
;forming the decoded image signal set into a plurality of N×
N overlapped image-data matrices comprising terms denoted by vs,r (j,i), in accordance with the relationship,
space="preserve" listing-type="equation">v.sub.s,r (j,i)=s.sub.R (j+ω
s, i+ω
r);transforming said overlapped image-data matrices into modified coefficient matrices comprising terms denoted by Svs,r (υ
,μ
), by means of an orthogonal transform basis matrix C in accordance with the matrix equation,
space="preserve" listing-type="equation">Sv.sub.s,r (υ
,μ
)=C×
v.sub.s,r (j,i)×
C.sup.T ;estimating the scaling factor κ
;determining filter parameters as a function of said scaling factor, said filter parameters denoted by α
(κ
) and η
(κ
);selecting a quantization error matrix, denoted by E0 ; converting said modified coefficient matrices into filtered coefficient matrices by means of said quantization error matrix and said filter parameters, said modified coefficient matrix comprising terms denoted by Sfs,r (υ
,μ
), said step of converting said modified coefficient matrices performed in accordance with the equation, ##EQU27## transforming said filtered coefficient matrices into filtered image-data matrices, denoted by rfs,r (j,i), in accordance with the matrix equation,
space="preserve" listing-type="equation">rf.sub.s,r (j,i)=C.sup.T ×
Sf.sub.s,r (υ
,μ
)×
C; andconverting said filtered image-data matrices into a series of filtered electrical signals such that said filtered electrical signals can be configured into a two-dimensional H×
V array of filtered image elements to form a reduced-noise digital image, each said filtered electrical signal corresponding to a characteristic of one said filtered image element. - View Dependent Claims (19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29)
- and quantization terms derived from a quantization table, and where the decoded image signal has been configured as a two-dimensional H×
-
30. A method for filtering a two-dimensional decoded image signal such that the effects of blocking artifacts attributable to quantization are reduced, the blocking artifacts arising in the decoded image signal as a consequence of there having been performed transform image coding, data compression, and quantization on an antecedent image signal, the antecedent image signal having been provided as a series of electrical signals, each electrical signal corresponding to a characteristic of an element of the antecedent image, where the compression operation utilized a scaling factor and quantization terms obtained from a quantization table, and where the decoded image signal has been configured as a two-dimensional H×
- V set of image-data terms denoted by sR (z,y), said method comprising the steps of;
converting said set of image-data terms into a plurality of frequency coefficient terms by means of an orthogonal transform basis matrix; filtering said plurality of frequency coefficient terms by means of a filtering computation, said filtering computation comprising the step of multiplying said frequency coefficient terms with a coefficient filtering term to form a plurality of filtered frequency coefficient terms; and converting said filtered frequency coefficients into a reduced-noise digital image. - View Dependent Claims (31, 32, 33, 34, 35, 36, 37)
- V set of image-data terms denoted by sR (z,y), said method comprising the steps of;
-
38. An image processing apparatus for reducing the effects of blocking artifacts attributable to quantization incurred in the transform image coding and compression of a two-dimensional image signal into a digital image, the degree of compression determined by a scaling factor and a quantization table, and the image signal provided as a series of electrical signals, each electrical signal corresponding to a characteristic of an element of a two-dimensional image, where the image elements have been configured as a two-dimensional H×
- V array, said apparatus comprising;
means for applying an orthogonal transform basis matrix to the two-dimensional H×
V array of image elements so as to form a coded image-data set comprising quantized terms;means for applying said orthogonal transform basis matrix to said coded image-data set so as to form a decoded image-data set; means for transform image coding said decoded image-data set into a plurality of frequency coefficient terms; filtering means, operative on said frequency coefficient terms such that said frequency coefficient terms are multiplied by a coefficient filtering term to form a plurality of filtered frequency coefficient terms; and means for converting said filtered frequency coefficients into a reduced-noise digital image. - View Dependent Claims (39, 40, 41, 42, 43, 44, 45)
- V array, said apparatus comprising;
-
46. An image processing apparatus for filtering a two-dimensional decoded image signal such that the effects of blocking artifacts attributable to quantization are reduced, the blocking artifacts arising in the decoded image signal as a consequence of there having been performed transform image coding, data compression, and quantization on an antecedent image signal, the antecedent image signal having been provided as a series of electrical signals, each electrical signal corresponding to a characteristic of an element of the antecedent image, where the compression operation utilized a scaling factor and quantization terms obtained from a quantization table, and where the decoded image signal has been configured as a two-dimensional H×
- V set of image-data terms denoted by SR (z,y), said apparatus comprising;
means for transform image coding said set of image-data terms into a plurality of frequency coefficient terms by means of an orthogonal transform basis matrix; filtering means, operative on said frequency coefficient terms such that said frequency coefficient terms are multiplied by a coefficient filtering term to form a plurality of filtered frequency coefficient terms; and means for converting said filtered frequency coefficients into a reduced-noise digital image. - View Dependent Claims (47, 48, 49, 50, 51, 52)
- V set of image-data terms denoted by SR (z,y), said apparatus comprising;
Specification