TECHNIQUES FOR LOW-LIGHT IMAGING
In one example, a method of image processing includes acquiring a plurality of input image frames, detecting at least one object of interest in individual image frames of the plurality of image frames, for the individual image frames, producing a respective bounding box corresponding to the at least one object of interest, the bounding box describing coordinates of a boundary of the object of interest within a respective individual image frame, temporally averaging corresponding pixel values of pixels within the bounding box over the plurality of image frames to produce a plurality of averaged pixel values, and producing an output image in which pixels within an area of the output image described by coordinates of the bounding box are replaced with the averaged pixel values.
1 . A method of image processing, the method comprising:
acquiring a plurality of input image frames;
detecting at least one object of interest in individual image frames of the plurality of image frames;
for the individual image frames, producing a respective bounding box corresponding to the at least one object of interest, the bounding box describing coordinates of a boundary of the object of interest within a respective individual image frame;
temporally averaging corresponding pixel values of pixels within the bounding box over the plurality of image frames to produce a plurality of averaged pixel values; and
producing an output image in which pixels within an area of the output image described by coordinates of the bounding box are replaced with the averaged pixel values.
2 . The method of claim 1 , wherein producing the bounding box includes:
determining a center point and at least one sizing parameter of the bounding box in a first image frame of the plurality of image frames; and
constraining the center point of the bounding box in a second image frame of the plurality of image frames based at least in part on a weighting factor applied to the center point of the bounding box in the first image frame.
3 . The method of claim 1 , wherein detecting the at least one object of interest includes processing the individual image frames using one or more convolutional neural networks.
4 . The method of claim 1 , wherein producing the output image includes producing the output image including the bounding box positioned around the at least one object of interest.
5 . The method of claim 1 , wherein acquiring the plurality of input image frames includes accessing the plurality of input image frames from at least one non-transitory machine-readable storage medium.
6 . The method of claim 1 , wherein acquiring the plurality of input image frames includes receiving the plurality of input image frames from an imaging device, wherein the individual image frames are acquired by the imaging device under a very low light condition.
7 . The method of claim 1 , further comprising displaying the output image on a display.
8 . The method of claim 1 , wherein detecting the at least one object of interest and producing the respective bounding box comprises:
applying a spatial averaging filter to the individual image frames to produce corresponding individual filtered image frames;
determining the coordinates of the bounding box in a respective filtered image frame; and
applying the bounding box to the respective individual image frame.
9 . A computer program product including one or more non-transitory machine-readable mediums having instructions encoded thereon that when executed by at least one processor cause an image processing method to be carried out, the method comprising:
acquiring a plurality of input image frames;
detecting at least one object of interest in individual image frames of the plurality of image frames;
for the individual image frames, producing a respective bounding box corresponding to the at least one object of interest, the bounding box describing coordinates of a boundary of the object of interest within a respective individual image frame;
temporally averaging corresponding pixel values of pixels within the bounding box over the plurality of image frames to produce a plurality of averaged pixel values; and
producing an output image in which pixels within an area of the output image described by coordinates of the bounding box are replaced with the averaged pixel values.
10 . The computer program product of claim 9 , wherein producing the bounding box includes:
determining a center point and at least one sizing parameter of the bounding box in a first image frame of the plurality of image frames; and
constraining the center point of the bounding box in a second image frame of the plurality of image frames based at least in part on a weighting factor applied to the center point of the bounding box in the first image frame.
11 . The computer program product of claim 9 , wherein detecting the at least one object of interest includes processing the individual image frames using one or more convolutional neural networks.
12 . The computer program product of claim 9 , wherein producing the output image includes producing the output image including the bounding box positioned around the at least one object of interest.
13 . The computer program product of claim 9 , wherein acquiring the plurality of input image frames includes accessing the plurality of input image frames from at least one non-transitory machine-readable storage medium.
14 . An image sensor comprising:
an imaging device configured to acquire a temporal series of image frames; and
a digital signal processing module coupled to the imaging device and configured to
process the image frames to detect at least one object of interest in individual image frames of the image frames,
for the individual image frames, produce a respective bounding box corresponding to the at least one object of interest, the bounding box describing coordinates of a boundary of the object of interest within a respective individual image frame,
average corresponding pixel values of pixels within the bounding box over the temporal series of image frames to produce a plurality of averaged pixel values, and
produce an output image in which at least some pixels within an area of the output image described by coordinates of the bounding box are replaced with the averaged pixel values.
15 . The image sensor of claim 14 , wherein to produce the bounding box, the digital signal processing module is configured to:
determine a center point and at least one sizing parameter of the bounding box in a first image frame of the plurality of image frames; and
constrain the center point of the bounding box in a second image frame of the plurality of image frames based at least in part on a weighting factor applied to the center point of the bounding box in the first image frame.
16 . The image sensor of claim 14 , wherein to detect the at least one object of interest, the digital signal processing module is configured to process the individual image frames using one or more convolutional neural networks.
17 . The image sensor of claim 14 , wherein to produce the output image, the digital signal processing module is configured to produce the output image including the bounding box positioned around the at least one object of interest.
18 . The image sensor of claim 14 , further comprising a display coupled to the digital signal processing module and configured to display the output image.
19 . The image sensor of claim 14 , wherein the imaging device is configured to acquire the image frames at a frame rate of between 45 and 90 frames per second.
20 . The image sensor of claim 14 , wherein to detect the at least one object of interest and to produce the respective bounding box, the digital signal processing module is configured to:
apply a spatial averaging filter to the individual image frames to produce corresponding individual filtered image frames;
determine the coordinates of the bounding box in a respective filtered image frame; and
apply the bounding box to the respective individual image frame.