1. A computer-implemented process for encoding multiple video signals comprising the process actions of:
capturing streams of images of the same event from different views simultaneously using two or more cameras;
for views captured at the same time, using camera parameters to decompose all views into a three dimensional (3D) mapping for a set of feature points;
predicting a mapping of the set of feature points for all views at a current time instant from a set of reconstructed feature points from previous views at a previous time instant;
calculating a first order difference between the predicted mapping of the set of feature points and original feature points decomposed from views at said current time instant;
transforming the first order difference to decompose spatial correlations;
quantizing the transformed first order difference;
entropy encoding the quantized transformed first order difference as a base layer;
reconstructing a reconstructed set of feature points through dequantizing, inverse transforming the quantized transformed first order difference, and adding it to the predicted set of feature points;
mapping each of said reconstructed feature points back onto each view from which it was extracted to form a synthesized predicted view image for each view;
calculating the difference between the synthesized predicted view image and the captured image for each view to obtain a predicted enhancement residue;
predicting a second-order difference between the predicted enhancement residue at the current time instant and a stored reconstructed enhancement residue at the previous time instant to decompose temporal correlations of residuals of each view image;
transforming the second-order difference to decompose spatial correlations of residuals of each view;
quantizing the transformed second-order difference; and
entropy encoding the transformed quantized second-order difference as an enhancement layer which when combined with the base layer represents the encoded image stream.
2. The computer-implemented process of claim 1 wherein the captured streams of images have previously been compressed.
3. The computer-implemented process of claim 1 wherein the captured streams of images have not previously been compressed.
4. The computer-implemented process of claim 1 wherein the three dimensional (3D) mapping for a set of feature points comprises for each feature point a set of three dimensional coordinates and corresponding color components.
5. The computer-implemented process of claim 4 wherein the three dimensional coordinates are expressed in a three dimensional Cartesian coordinate system.
6. The computer-implemented process of claim 4 wherein the color components are defined in Y, U, V color space.
7. The computer-implemented process of claim 1 wherein a view is decoded by the following process actions:
inputting an encoded image comprising a base layer for all views and an enhancement layer for a certain view;
decoding the base layer by:
entropy decoding the encoded base layer of the input image,
dequantizing the entropy decoded base layer of the input image;
inverse transforming the entropy decoded dequantized base layer to obtain a residual of a set of predicted feature points;
adding the residual onto the mapping of the set of predicted feature points to obtain the reconstructed feature points.
decoding the enhancement layer by:
entropy decoding the encoded enhancement layer of the input image,
dequantizing the entropy decoded enhancement layer of the input image;
inverse transforming the entropy decoded dequantized enhancement layer to obtain entropy decoded dequantized inverse transformed second order residuals;
adding the entropy decoded dequantized inverse transformed enhancement second-order residuals onto the predicted enhancement residual to obtain the reconstructed enhancement residual;
inverse mapping the set of feature points obtained from the decoded base layer to a given view to obtain an interim image;
reconstructing the image of the given view by adding the reconstructed enhancement residual to the interim image.
8. The computer-implemented process of claim 7 wherein the base layer bit stream is organized such that only feature points required for a certain view are decoded.
9. The computer-implemented process of claim 8 wherein all feature points are contained in a cloud and wherein said cloud is partitioned into boxes and wherein feature points in a given box are regarded as a sub-cloud and decoded independently.
10. The computer-implemented process of claim 9 wherein only the sub-clouds are decoded that are necessary to decode the bit stream for a certain view.
11. The computer-implemented process of claim 8 wherein the boxes are of unequal size.
12. The computer-implemented process of claim 8 wherein the boxes are of equal size.
13. A computer-implemented process for encoding multiple video signals comprising the process actions of:
capturing images from different views at the ith time;
for views captured at the ith time, with known corresponding cameras’ positions, extracting a feature points set Mi.
predicting mapping information for the set of feature points Mi from a stored feature point set {circumflex over (M)}i\u22121 to remove temporal correlations from the set of feature points Mi;
transforming Mi\u2212{circumflex over (M)}i\u22121;
quantizing transformed Mi\u2212{circumflex over (M)}i\u22121;
entropy coding the transformed, quantized Mi\u2212{circumflex over (M)}i\u22121 to generate a base layer bit stream;
inverse mapping the predicted mapping information for {circumflex over (M)}i using the cameras’ positions to obtain a predicted image for each view;
determining the difference between the predicted image and the view captured for each ith time;
predicting a second-order difference of each view between the said difference for each ith time and a stored difference for each i\u22121th time to remove temporal correlations;
transforming the second-order difference;
quantizing the transformed second-order difference; and
entropy encoding the second-order difference for each ith time to generate enhancement layer bit streams for each view.
14. The computer-implemented process of claim 13 wherein at least one transform employs a Discrete Cosine Transform (DCT) technique.
15. The computer-implemented process of claim 13 wherein at least one transform employs a Discrete Wavelet Transform (DWT) technique.
16. The computer-implemented process of claim 13 wherein the stored feature point set {circumflex over (M)}i\u22121 is a previous reconstructed feature point set.
17. The computer-implemented process of claim 13 wherein each feature point is expressed as a set of three dimensional coordinates and corresponding color components.
18. A system for decoding a video signal, comprising:
a general purpose computing device;
a computer program comprising program modules executable by the general purpose computing device, wherein the computing device is directed by the program modules of the computer program to,
input an encoded image comprising a base layer for all views and an enhancement layer for a certain view;
decode the base layer by:
entropy decoding the encoded base layer of the input image,
dequantizing the entropy decoded base layer of the input image;
inverse transforming the entropy decoded dequantized base layer to obtain a residual of a set of predicted feature points expressed as a set of three dimensional coordinates and corresponding color components;
adding the residual onto the predicted feature points to obtain the reconstructed feature points.
decode the enhancement layer by:
entropy decoding the encoded enhancement layer of the input image,
dequantizing the entropy decoded enhancement layer of the input image;
inverse transforming the entropy decoded dequantized enhancement layer to obtain inverse transformed entropy decoded dequantized second order residua;
adding the entropy decoded dequantized inverse transformed enhancement second-order residua onto the residual of the set of predicted feature points to obtain the reconstructed enhancement residua;
inverse map the set of feature points obtained from the decoded base layer to a given view to attain an interim image;
reconstruct an image of the given view by adding the reconstructed enhancement residua to the interim image.
19. A computer-readable medium having computer executable instructions for encoding more than one video stream, said computer executable instructions comprising:
inputting captured images from different views of the same event space at the ith time;
for views captured at the ith time, with known corresponding cameras’ positions, extracting a feature points set Mi, each feature point being expressed as a set of three dimensional coordinates and corresponding color components;
predicting mapping information for the set of feature points Mi from a stored feature point set {circumflex over (M)}i\u22121 to remove temporal correlations from the set of feature points Mi;
transforming Mi\u2212{circumflex over (M)}i\u22121;
quantizing the transformed Mi\u2212{circumflex over (M)}i\u22121;
entropy coding the transformed, quantized Mi\u2212{circumflex over (M)}i\u22121 to generate a base layer bit stream;
inverse mapping the predicted mapping information for {circumflex over (M)}i using the cameras’ positions to obtain a predicted image for each view;
determining the difference between the predicted image and the view captured for each ith time;
predicting a second-order difference between the difference for each ith time and a stored difference for each i\u22121th time to remove temporal correlations;
transforming the second-order difference;
quantizing the transformed second-order difference; and
entropy encoding the transformed quantized second-order difference for each ith time to generate enhancement layer bit streams for each view.
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. An imaging detection system comprising:
at least one location detection device configured to determine coordinates of a target;
at least one detector configured to detect events from a source associated with the target; and
a processor coupled in communication with said at least one location detection device and said at least one detector, said processor configured to:
receive the coordinates from said at least one location detection device and the events from said at least one detector;
translate the events using the coordinates acquired from said at least one location detection device to compensate for a relative motion between the source and said at least one detector; and
output a processed data set having the events translated based on the coordinates.
2. An imaging detection system in accordance with claim 1 wherein said at least one detector is configured to detect a direction from the source to said at least one detector.
3. An imaging detection system in accordance with claim 1 wherein the event is a discrete emission of radiation, said at least one detector comprising a radiation detector configured to detect the discrete emission of radiation.
4. An imaging detection system in accordance with claim 1 wherein the event is an interval of a continuously variable signal, said at least one detector configured to detect the continuously variable signal.
5. An imaging detection system in accordance with claim 1 wherein said processor is configured to compensate for a change in pose of the target with respect to said at least one detector.
6. An imaging detection system in accordance with claim 1 wherein said at least one location detection device comprises a camera.
7. An imaging detection system in accordance with claim 1 wherein said at least one location detection device comprises a plurality of cameras configured to acquire real-time video.
8. An imaging detection system in accordance with claim 1 wherein said at least one detector comprises a Compton imaging detector.
9. An imaging detection system in accordance with claim 1 wherein said at least one location detection device is configured to transmit a location of the target in three-dimensional real-world coordinates.
10. An imaging detection system comprising:
a tracking system comprising a location detection device, said tracking system configured to determine coordinates of a target based on data acquired from said location detection device;
a detection system comprising a detector, said detection system configured to detect events from a source associated with the target based on data acquired from said detector; and
a processor coupled in communication with said tracking system and said detection system, said processor configured to:
receive the coordinates from said tracking system and the events from said detection system;
translate the events using the coordinates from said tracking system to compensate for a relative motion between the source and said detector; and
output a processed data set having the events translated based on the coordinates.
11. An imaging detection system in accordance with claim 10 wherein a plurality of targets are positioned within a field of view of said imaging detection system, said processor configured to translate all detected events for each target of the plurality of targets.
12. An imaging detection system in accordance with claim 10 wherein said detection system is configured to autonomously detect the source and determine whether the source is at least one of a naturally-occurring radioactive material, background, a medical isotope, and potential contraband.
13. An imaging detection system in accordance with claim 10 wherein said detection system comprises an orientation sensor configured to continuously transform detected directional data into real-world coordinates of said detector.
14. An imaging detection system in accordance with claim 10 wherein said processor is configured to apply a rotation matrix to each point in an initial array of points to rotate each point in the initial array of points based on the coordinates.
15. A method for generating an image of a source moving with respect to a detector, the method comprising:
acquiring real-world coordinates of a target associated with the source using a location detection device;
detecting events from the source using the detector;
translating the events using the real-world coordinates to compensate for a relative motion between the source and the detector; and
generating the image having the events translated to intersect generally at a center of a field of view of the image.
16. A method in accordance with claim 15 wherein the detected events form an initial array of points, translating the events further comprises transforming each point in the initial array of points into a movement-compensated point.
17. A method in accordance with claim 16 wherein transforming each point in the initial array of points further comprises applying a rotation matrix to each point in the initial array of points to rotate each point in the initial array of points based on the real-world coordinates.
18. A method in accordance with claim 15 further comprising weighting a signal associated with each translated event.
19. A method in accordance with claim 18 wherein weighting a signal further comprises weighting the signal based on a certainty of the associated event.
20. A method in accordance with claim 15 wherein a plurality of targets are within a field of view of the detector, said method further comprising translating the events for each target using real-world coordinates of each target to compensate for a relative motion between each target and the detector.