1. A method for reliability estimation of temporal noise estimation in a sequence of video frames, comprising the steps of:
obtaining temporal local differences from the difference between a previous frame and a next frame in the sequence of frames;
determining a distribution of the temporal local difference;
determining characteristic values of the distribution; and
comparing the characteristic values to one or more thresholds to obtain an indication of the reliability of the temporal noise estimation.
2. The method of claim 1 wherein the step of determining said distribution further comprises determining the histogram of the temporal local difference.
3. The method of claim 1 further comprising the steps of determining said difference between the previous frame and the next frame in the sequence of frames.
4. The method of claim 1 wherein the steps of determining characteristic values of the distribution further includes the steps of determining a characteristic value m1 as a reliability measurement, by computing:
m
1
=
\u2211
y
^
=
0
2
\u2062
y
^
p
\u2062
h
\u2061
(
y
^
)
.
where \u0177 represents the MAE of said temporal local difference;
h(\u0177) represents said histogram (distribution); and
\u0177p is an MAE value corresponding to the maximum value of h(\u0177).
5. The method of claim 4, further comprising the steps of determining \u0177p as the MAE value corresponding to the maximum value of h(\u0177) by computing:
y
^
p
=
arg
\u2062
\u2003
\u2062
max
y
^
\u2062
h
\u2061
(
y
^
)
.
6. The method of claim 1 wherein the steps of determining characteristic values of the distribution further includes the steps of determining a characteristic value m2 as a reliability measurement, by computing:
m
2
=
\u2211
y
^
=
3
4
\u2062
y
^
p
5
4
\u2062
y
^
p
\u2062
h
\u2061
(
y
^
)
\u2211
y
^
=
0
2
\u2062
y
^
p
\u2062
h
\u2061
(
y
^
)
,
where \u0177 represents the MAE of said temporal local difference;
h(\u0177) represents said histogram (distribution); and
\u0177p represents the MAE value corresponding to the maximum value of h(\u0177).
7. The method of claim 1 wherein the steps of determining characteristic values of the distribution further includes the steps of determining a characteristic value m3 as a reliability measurement, by computing:
m
3
=
\u2211
y
^
=
1
2
\u2062
y
^
p
y
^
p
\u2062
(
y
^
p
–
y
^
)
\xb7
h
\u2061
(
y
^
)
y
^
p
\xb7
\u2211
y
^
=
1
2
\u2062
y
^
p
y
^
p
\u2062
h
\u2061
(
y
^
)
,
where \u0177 represents the MAE of said difference;
h(\u0177) represents said histogram (distribution); and
\u0177p represents the MAE value corresponding to the maximum value of h(\u0177).
8. A method for reliability estimation of temporal noise estimation in a sequence of video frames, comprising the steps of:
determining a plurality of reliability estimates; and
combining the plurality of reliability estimations to generate a combined reliability estimate.
9. The method of claim 8, wherein the step of determining each reliability estimate further comprises the steps of:
obtaining the temporal local differences from the difference between a previous frame and a next frame in the sequence of frames;
determining a distribution of the temporal local difference;
determining characteristic values of the distribution; and
comparing the characteristic values to one or more thresholds to obtain an indication of the reliability of the temporal noise estimation.
10. A reliability estimator for determining reliability estimation of temporal noise estimation in a sequence of video frames, comprising:
a differencing means that determines the temporal local differences from the difference between a previous frame and a next frame in the sequence of frames;
a distribution calculator that determines a distribution of the temporal local difference;
a characteristic value calculator that determines statistical characteristic values of the distribution; and
a reliability detector that compares the characteristics values to one or more thresholds to obtain an indication of the reliability of the temporal noise estimation.
11. The reliability estimator of claim 10 wherein the distribution calculator step determines the histogram of the temporal local difference.
12. The reliability estimator of claim 10 wherein the differencing means further determines said difference between the previous frame and the next frame.
13. The reliability estimator of claim 10 wherein the characteristic value calculator determines a characteristic value m1 as a reliability measurement, by computing:
m
1
=
\u2211
y
^
=
0
2
\u2062
y
^
p
\u2062
h
\u2061
(
y
^
)
,
where \u0177 represents the MAE of said temporal local difference;
h(\u0177) represents said histogram (distribution); and
\u0177p is a function of the MAE value corresponding to the maximum value of h(\u0177).
14. The reliability estimator of claim 13, wherein the characteristic value calculator further determines \u0177p as the MAE value corresponding to the maximum value of h(\u0177) by computing:
y
^
p
=
arg
\u2062
\u2003
\u2062
max
y
^
\u2062
h
\u2061
(
y
^
)
.
15. The reliability estimator claim 10 wherein the characteristic value calculator determines a characteristic value m2 as a reliability measurement, by computing:
m
2
=
\u2211
y
^
=
3
4
\u2062
y
^
p
5
4
\u2062
y
^
p
\u2062
h
\u2061
(
y
^
)
\u2211
y
^
=
0
2
\u2062
y
^
p
\u2062
h
\u2061
(
y
^
)
,
where \u0177 represents the MAE of said temporal local difference;
h(\u0177) represents said histogram (distribution); and
\u0177p represents the MAE value corresponding to the maximum value of h(\u0177).
16. The reliability estimator of claim 10 wherein the characteristic value calculator determines a characteristic value m3 as a reliability measurement, by computing:
m
3
=
\u2211
y
^
=
1
2
\u2062
y
^
p
y
^
p
\u2062
(
y
^
p
–
y
^
)
\xb7
h
\u2061
(
y
^
)
y
^
p
\xb7
\u2211
y
^
=
1
2
\u2062
y
^
p
y
^
p
\u2062
h
\u2061
(
y
^
)
,
where \u0177 represents the MAE of said difference;
h(\u0177) represents said histogram (distribution); and
\u0177p represents the MAE value corresponding to the maximum value of h(\u0177).
17. A reliability estimation system that determined reliability estimation of temporal noise estimation in a sequence of video frames, comprising:
a plurality of reliability estimators, wherein each reliability estimator determines a reliability estimate; and
a combiner that combines the reliability estimations from the reliability estimators to generate a combined reliability estimate.
18. The reliability estimation system of claim 17, wherein each reliability estimator comprises:
a differencing means that determines the temporal local differences from the difference between a previous frame and a next frame in the sequence of frames;
a distribution calculator that determines a distribution of the temporal local difference;
a characteristic value calculator that determines characteristics value of the distribution; and
a reliability detector that compares the characteristic values to one or more thresholds to obtain an indication of the reliability of the temporal noise estimation.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A method for processing noise interference in a data accessing device with a SATA (Serial Advanced Technology Attachment) interface, the method comprising:
an error detecting step for detecting whether there is a CRC (Cyclic Redundancy Check) error, whether an reception error primitive (R_ERR primitive) is received, whether an improper primitive is received, or whether a LINK layer error is detected, and repeating this step if there is no any error;
a type detecting step for detecting whether an incoming FIS (Frame Information Structure) is a data type FIS and going back to the error detecting step when the FIS is not data type;
a responding step for asserting the CHECK bit of the ATAPI Status Register when the incoming FIS is data type; and
sending back the response.
2. The method according to claim 1, wherein the responding step further comprising asserting the ABRT bit of the ATAPI Error Register.
3. The method according to claim 1, wherein the method is used in an optical storage device connected to the SATA interface.
4. The method according to claim 1, further comprising:
an ATAPI (AT Attachment with Packet Interface) packet command detecting step for detecting whether the incoming FIS is an ATAPI packet command when the FIS is data type, and executing the responding step if the FIS is the ATAPI packet command; and
a DMA (Direct Memory Access) mode data Iransfer detecting step for detecting whether there is a DMA mode data transfer when the data FIS is not the ATAPI packet command, and executing the responding step if there is not a DMA mode data transfer.
5. The method according to claim 4, wherein the method is used in an optical storage device connected to the SATA interface.
6. The method according to claim 4, further comprising:
a request sense command detecting step for detecting whether the present command is a request sense command when there is a DMA mode data transfer;
setting a sense key of the ATAPI Error Register to 11 and executing the responding step if the present command is the request sense command; and
setting the sense key of the ATAPI Error Register to 4 and executing the responding step if the present command is not the request sense command.
7. The method according to claim 6, wherein the method is used in an optical storage device connected to the SATA interface.
8. The method according to claim 1, wherein the error state detecting step is performed in a link layer.
9. The method according to claim 8, wherein the method is used in an optical storage device connected to the SATA interface.