Abstract: Embodiments of the present disclosure relate to encoding of junction area information in map data. In particular, the encoding may include organizing vehicle paths that traverse through a junction area according to path groups and organizing contentions that influence behavior of vehicles traveling along the vehicle paths according to contention groups. In addition, the encoding may include generating direction data structures that associate respective path groups with one or more of the contention groups. In these or other embodiments, the map data that corresponds to the junction area may be updated with direction data structures.

Abstract: Method and devices are disclosed for focusing on tilted image planes. For example, one imaging device includes an objective lens configured to focus a scene at an image plane, the scene having an object plane tilted relative to the objective lens plane and a sensor receive light from the objective lens, the sensor having a plurality of light sensing elements configured to generate image data based on the light received at the sensor. The imaging device also includes a processor and memory component configured to receive the image data, the image data indicative of a first image; receive a tilt parameter indicative of an orientation of a selected non-parallel image plane, and convert the image data to relative image data based on the tilt parameter, the relative image data indicative of a second image focused along the non-parallel image plane.

Abstract: A system and method for tone mapping on a high dynamic range (HDR) image of a scene are disclosed. In one embodiment, tone mapping on the HDR image is performed using a set of bit-depths, that corresponds to a plurality of images of the scene, obtained at each unit of an irradiance range of the scene.

Abstract: Method and devices are disclosed for focusing on tilted image planes. For example, one imaging device includes an objective lens configured to focus a scene at an image plane, the scene having an object plane tilted relative to the objective lens plane and a sensor receive light from the objective lens, the sensor having a plurality of light sensing elements configured to generate image data based on the light received at the sensor. The imaging device also includes a processor and memory component configured to receive the image data, the image data indicative of a first image; receive a tilt parameter indicative of an orientation of a selected non-parallel image plane, and convert the image data to relative image data based on the tilt parameter, the relative image data indicative of a second image focused along the non-parallel image plane.

Abstract: A method for generating a high dynamic range (HDR) image from images of a scene obtained at one or more exposure values is disclosed. In this embodiment, one of the obtained images is selected as a reference image. Further, mapped images are obtained by mapping pixel intensity values to corresponding irradiance values in each image. Furthermore, a pixel intensity value dependent weighting factor is determined. Moreover, a set of images is identified from the mapped images for pixels in the reference image. Also, a set of corresponding mapped pixels is established for the mapped pixels in reference image in the set of images. Further, a similarity measure is computed for the mapped pixels of reference image and corresponding mapped pixels in the set of images. Furthermore, each mapped pixel of the reference image is combined with a subset of its established corresponding mapped pixels in the set of images.

Abstract: A system and method for tone mapping on a high dynamic range (HDR) image of a scene are disclosed. In one embodiment, tone mapping on the HDR image is performed using a set of bit-depths, that corresponds to a plurality of images of the scene, obtained at each unit of an irradiance range of the scene.

Abstract: A method for generating a high dynamic range (HDR) image from images of a scene obtained at one or more exposure values is disclosed. In this embodiment, one of the obtained images is selected as a reference image. Further, mapped images are obtained by mapping pixel intensity values to corresponding irradiance values in each image. Furthermore, a pixel intensity value dependent weighting factor is determined. Moreover, a set of images is identified from the mapped images for pixels in the reference image. Also, a set of corresponding mapped pixels is established for the mapped pixels in reference image in the set of images. Further, a similarity measure is computed for the mapped pixels of reference image and corresponding mapped pixels in the set of images. Furthermore, each mapped pixel of the reference image is combined with a subset of its established corresponding mapped pixels in the set of images.