Abstract: In an example embodiment, a method, apparatus and computer program product are provided. The method includes computing a first cost volume for a light-field image. A first depth map comprising depth information of the plurality of sub-images of the light-field image is computed based on the first cost volume. A first view image comprising reconstruction information is reconstructed based on the depth information of the plurality of sub-images. A second cost volume corresponding to the first cost volume is computed based on the reconstruction information. The second cost volume is filtered based on the first view image to generate an aggregated cost volume. A second depth map is generated based on the aggregated cost volume. The second depth map facilitates generation of a second view image that is associated with a resolution higher than a resolution of the first view image.

Abstract: In an example embodiment, a method, apparatus and computer program product are provided. The method includes facilitating receipt of an image of a scene and determining a graph based on connecting nodes of the image. The nodes are either pixels or superpixels of the image. The graph is determined by determining one or more connections of a node to one or more nodes belonging to a pre-defined image region around the node in the image. The connections are associated with edge weights that are determined based on at least one of similarity parameters and spatial distances between the node and the one or more nodes. The method includes determining disparity values at the nodes of the image based at least on performing tree based aggregation of a cost volume on the graph, where the cost volume is associated with the image and at least one view image of the scene.

Abstract: In an example embodiment a method, apparatus and computer program product are provided. The method includes accessing feature points in a first frame of a content, and aligning a second frame to the first frame based on determining a transformation matrix between the second frame and the first frame based on matching the feature points in the first frame with a corresponding feature points in the second frame. The method further includes aligning at least one subsequent frame from the second frame to the first frame by generating a modified first frame based on a transformation matrix between a preceding frame of a subsequent frame and the first frame, and determining a transformation matrix between the subsequent frame and the first frame based on matching a set of feature points in the modified feature points with corresponding feature points in the subsequent frame.

Abstract: In an example embodiment a method, apparatus and computer program product are provided. The method includes facilitating receipt of a first and a second image. A first and a second aggregated cost volume associated with pixels of the first and the second images are determined for a plurality of disparity values. A first and a second disparity maps are generated based on the first and the second aggregated cost volume. A confidence map for disparity values of the first image is generated based on the first aggregated cost volume. One or more infinity regions in the first image are determined based on a number of confident pixels in color segments of the first image. A third disparity map is generated by determining filtered disparity values for the pixels of the first image where filtered disparity values for pixels of the one or more infinity regions are a pre-defined disparity value.

Abstract: In an example embodiment, a method, apparatus and computer program product are provided. The method includes facilitating receipt of primary depth map and plurality of color segments, the primary depth map associated with a first image and a second image that are stereoscopic pair of images of a scene, and the color segments associated with the first image. The method includes generating plurality of disparity planes based on the color segments and the primary depth map. The method includes determining aggregated cost volume between pixels of the first and second images for the disparity planes. The method includes assigning plane labels corresponding to the disparity planes to pixels of the first and second images based on the aggregated cost volume, an individual pixel being assigned a plane label. The method includes generating secondary depth map based on the plane labels assigned to the pixels of the first and second images.

Abstract: In an example embodiment, a method, apparatus and computer program product are provided. The method includes facilitating access of a first image and a second image associated with a scene. The first image and the second image includes depth information and at least one non-redundant portion. A first disparity map of the first image is computed based on the depth information associated with the first image. At least one region of interest (ROI) associated with the at least one non-redundant portion is determined in the first image based on the depth information associated with the first image. A second disparity map of at least one region in the second image corresponding to the at least one ROI of the first image is computed. The first disparity map and the second disparity map are merged to estimate an optimized depth map of the scene.

Abstract: In an example embodiment, a method, apparatus and computer program product are provided. The method includes facilitating receipt of a first image and a second image of a scene comprising one or more objects. The method includes detecting the objects in the first image by detecting object point of the objects in the first image. The method includes detecting the object points of the objects in the second image based on detection of the object points of the objects in the first image. Detection of an object point in the second image that corresponds to an object point of the first image comprises searching for the object point on an epipolar line in the second image corresponding to the object point of the first image. The method includes determining disparity values between the objects points in the first image and the object points in the second image.

Abstract: In accordance with an example embodiment a method, apparatus and computer program product are provided. The method comprises filtering incident light by an IR cut-off filter to generate filtered light. The IR cut-off filter comprises a plurality of pixels with pass-band characteristics for visible light wavelengths and is configured to perform stop-band attenuation of near infrared (NIR) wavelengths. The stop-band attenuation is configured to vary based on spatial location of pixels within the IR cut-off filter. The filtered light received from the IR cut-off filter is sensed by the image sensor to generate sensed light. A baseband signal and a modulated NIR signal are determined by performing transformation of the sensed light. A NIR spectrum associated with the incident light is determined by demodulating the modulated NIR signal. A visible spectrum associated with the incident light is determined based on the NIR spectrum and the baseband signal.

Abstract: In accordance with various example embodiments, methods, apparatuses, and computer program products are provided. A method comprises receiving a panchromatic image of a scene captured from a panchromatic image sensor, receiving a colour image of the scene captured from a colour image sensor, and generating a modified image of the scene based at least in part on processing the panchromatic image and the colour image. The apparatus comprises at least one processor and at least one memory, configured to, cause the apparatus to perform receiving a panchromatic image of a scene captured from a panchromatic image sensor, receiving a colour image of the scene captured from a colour image sensor, and generating a modified image of the scene based at least in part on processing the panchromatic image and the colour image.

Abstract: Methods and apparatuses are provided for capturing an image. A method may include determining a scene to be captured at a first resolution. The scene to be captured may be within a field of view of an image sensor. The method may further include causing capture by the image sensor of a plurality of sub-images at a second resolution. The second resolution may be less than the first resolution. Each of the plurality of sub-images may depict a portion of the scene to be captured. The method may additionally include using the plurality of sub-images to generate an output image depicting the scene to be captured at the first resolution. Corresponding apparatuses are also provided.

Abstract: In accordance with an example embodiment a method and apparatus is provided. The method comprises receiving an image and a subsequent image having an overlapping region in a storage. The overlapping region comprises a first and a second overlapping region. A substantial portion of the second overlapping region in the subsequent image may be blended with a substantial portion of a non-overlapping region of the subsequent image, and then modified in the image based on the substantial portion of the blended second overlapping region in the subsequent image. A portion of the panorama image may be generated by combining the modified substantial portion of the second overlapping region with the substantial portion of the non-overlapping region of the image. The modified substantial portion of the second overlapping region and the substantial portion of the non-overlapping region of the image may be removed from the storage.

Abstract: In accordance with an example embodiment a method, apparatus and computer program product are provided. The method comprises determining a plurality of first pixels having resemblance with a second pixel associated with an image based on a depth information of the image. The method further comprises replacing the second pixel by at least one first pixel of the plurality of first pixels based on a determination that the at least one first pixel is not associated with the at least one image defect.

Abstract: An apparatus for generating a panoramic image(s) may include a processor and memory storing executable computer code causing the apparatus to at least perform operations including generating a panoramic image(s) based on performing registration on at least two images associated with depth map data and determining an overlap region(s) between the two images within first and second items of depth map data. The computer program code may further cause the apparatus to label the overlap region(s) within the first or second item of depth map data based on generating a virtual seam(s) connecting portions of the two images to generate a composite image. The portions correspond to image data within first and second items of depth map data. The computer program code may further cause the apparatus to blend the seam of the composite image to obtain the panoramic image. Corresponding methods and computer program products are also provided.

Abstract: In accordance with an example embodiment a method, apparatus and computer program product are provided. The method comprises determining a set of first-side edge portions and a set of second-side edge portions associated with a plurality of images. A first plurality of edge pairs is determined between the set of first-side edge portions and the set of second-side edge portions. A first set of weights are assigned to the first plurality of edge pairs based at least on a pair-wise matching between the set of first-side edge portions and the set of second-side edge portions. The plurality of images are arranged in a first sequence based on the first set of weights.

Abstract: In an example embodiment a method, apparatus and computer program product are provided. The method includes facilitating selection of a region of interest (ROI) in a plurality of frames of a multimedia content. The ROI is associated with a motion of at least one object. An object mobility data matrix associated with the ROI is determined in the plurality of frames. The object mobility data matrix is indicative of a difference in motion of the at least one object in the plurality of frames. A projection of the object mobility data matrix is determined on a line. The motion of the at least one object in the ROI is determined across the plurality of frames to as a periodic motion or a non-periodic motion based on the projection of the object mobility data matrix.

Abstract: In accordance with an example embodiment a method, apparatus and computer program product are provided. The method comprises receiving a first set of frames corresponding to a scene captured by a color image sensor and a second set of frames corresponding to the scene captured by a panchromatic image sensor. A number of frames in the second set is greater than a number of frames in the first set. The method further comprises generating color frames corresponding to the scene at a frame rate higher than a frame rate of the first set of frames based at least in part on processing of the first set of frames and the second set of frames.

Abstract: In an example embodiment a method, apparatus and computer program product are provided. The method includes accessing feature points in a first frame of a content, and aligning a second frame to the first frame based on determining a transformation matrix between the second frame and the first frame based on matching the feature points in the first frame with a corresponding feature points in the second frame. The method further includes aligning at least one subsequent frame from the second frame to the first frame by generating a modified first frame based on a transformation matrix between a preceding frame of a subsequent frame and the first frame, and determining a transformation matrix between the subsequent frame and the first frame based on matching a set of feature points in the modified feature points with corresponding feature points in the subsequent frame.

Abstract: Method, apparatus, and computer program product are provided. The method includes computing a first difference image for a first eye region based on a difference of red pixel intensity and green pixel intensity of each of a first set of pixels associated with the first eye region. The method further includes determining a first eye color defect region by computing a neighborhood processed first difference image by processing the first difference image, computing a first central point of the neighborhood processed first difference image based on a weighted centroid of red pixels associated with the neighborhood processed first difference image, and thereafter computing the first eye color defect region based on the first central point, and the red pixels associated with the first difference image.

Abstract: Methods and apparatuses are provided for capturing an image. A method may include determining a scene to be captured at a first resolution. The scene to be captured may be within a field of view of an image sensor. The method may further include causing capture by the image sensor of a plurality of sub-images at a second resolution. The second resolution may be less than the first resolution. Each of the plurality of sub-images may depict a portion of the scene to be captured. The method may additionally include using the plurality of sub-images to generate an output image depicting the scene to be captured at the first resolution. Corresponding apparatuses are also provided.

Abstract: In accordance with an example embodiment a method and apparatus is provided. The method comprises receiving an image and a subsequent image having an overlapping region in a storage. The overlapping region comprises a first and a second overlapping region. A substantial portion of the second overlapping region in the subsequent image may be blended with a substantial portion of a non-overlapping region of the subsequent image, and then modified in the image based on the substantial portion of the blended second overlapping region in the subsequent image. A portion of the panorama image may be generated by combining the modified substantial portion of the second overlapping region with the substantial portion of the non-overlapping region of the image. The modified substantial portion of the second overlapping region and the substantial portion of the non-overlapping region of the image may be removed from the storage.