Abstract: In various examples, a technique for removing residual IR estimated locally at a pixel in an image and performing corresponding color correction operations locally at the same pixel is disclosed. The technique includes receiving a first image captured using an image sensor. The technique also includes removing, from a first pixel in the first image, a contribution of infrared radiation to a color channel of the first pixel based at least on an estimated amount of residual infrared radiation. The technique also includes performing a first part of local color correction for the color channel of the first pixel based at least on the estimated amount of residual infrared radiation. The technique also includes performing global color correction for a plurality of pixels in a second image that is reconstructed from the first image, where the global color correction includes a second part of the local color correction.

Abstract: In various examples, metadata-based image harmonization for image stitching systems and applications are disclosed. Systems and methods are disclosed that preprocess images with respect to rendering parameters, with the effect of blending those parameters at a border between images to facilitate a smooth rendering when those images are stitched together. An image signal processing (ISP) parameter harmonization function may input metadata parameters associated with a set of images to match and blend one or more of the rendering parameters across an overlapping border between images prior to applying those images to a stitching algorithm. A scaling of the metadata parameter may be performed using a parameter gain function. Pixels in both images located along the border are adjusted to the same boundary metadata parameter value, and smoothed based on the parameter gain function. A discontinuity in rendering parameters is avoided, substantially avoiding corresponding artifacts in the resulting stitched image.

Abstract: In various examples, metadata-based image harmonization for image stitching systems and applications are disclosed. Systems and methods are disclosed that preprocess images with respect to rendering parameters, with the effect of blending those parameters at a border between images to facilitate a smooth rendering when those images are stitched together. An image signal processing (ISP) parameter harmonization function may input metadata parameters associated with a set of images to match and blend one or more of the rendering parameters across an overlapping border between images prior to applying those images to a stitching algorithm. A scaling of the metadata parameter may be performed using a parameter gain function. Pixels in both images located along the border are adjusted to the same boundary metadata parameter value, and smoothed based on the parameter gain function. A discontinuity in rendering parameters is avoided, substantially avoiding corresponding artifacts in the resulting stitched image.

Abstract: In various examples, an image processing pipeline may toggle between IR and RGB imaging modes in response to different thresholds of detected light intensity that depend on the toggling direction (e.g., a lower intensity threshold to switch from RGB to IR imaging and a higher intensity threshold to switch from IR to RGB imaging). For example, the image processing pipeline may switch from RGB to IR imaging in response to detecting an amount of light intensity (e.g., average intensity in a green channel) below a first threshold, and the image processing pipeline may switch from IR to RGB imaging in response to: (i) detecting an amount of light intensity (e.g., average intensity in a green channel) that exceeds a second threshold, and/or (ii) detecting a ratio of detected light intensities (e.g., IR to green) below a third threshold.

Abstract: Apparatuses, systems, and techniques to perform effective tone management for image data. In an embodiment, a set of contrast gain curves are generated corresponding to a set of tonal ranges of an input image. An output image may then be generated by at least applying corresponding contrast gain curves to tonal ranges of the input image.

Abstract: In various examples, apparatuses, systems, and techniques to perform offline image signal processing of source image data to generate target image data. In at least one embodiment, data collection using exposure and calibration setting of an image sensor is performed to generate source image data, which is then processed by using offline image signal processing to generate target data.

Abstract: In order to more accurately white balance an image, weightings can be determined for pixels of an image when computing an illuminant color value of the image and/or a scene. The weightings can be based at least in part on the Signal-to-Noise Ratio (SNR) of the pixels. The SNR may be actual SNR or SNR estimated from brightness levels of the pixels. SNR weighting (e.g., SNR adjustment) may reduce the effect of pixels with high noise on the computed illuminant color value. For example, one or more channel values of the illuminant color value can be determined based on the weightings and color values of the pixels. One or more color gain values can be determined based on the one or more channel values of the illuminant color value and used to white balance the image.

Abstract: Apparatuses, systems, and techniques to perform effective tone management for image data. In an embodiment, a set of contrast gain curves are generated corresponding to a set of tonal ranges of an input image. An output image may then be generated by at least applying corresponding contrast gain curves to tonal ranges of the input image.

Abstract: Apparatuses, systems, and techniques to perform effective tone management for image data. In an embodiment, a set of contrast gain curves are generated corresponding to a set of tonal ranges of an input image. An output image may then be generated by at least applying corresponding contrast gain curves to tonal ranges of the input image.

Abstract: The various embodiments of the present disclosure are directed towards methods for tone mapping High-Dynamic-Range (HDR) image data, as well as controlling the brightness of the image encoded by HDR the image data and/or the tone-mapped image data. HDR image is captured. A tone mapping function for the HDR image data is generated. To generate the tone mapping function, control points are dynamically determined based on an analysis of the HDR image data. The tone mapping function is fit to the control points. The tone mapping function is a non-linear function, and is described by a curve in a plane. The shape of the curve is constrained by a line generated from a portion of the control points. The tone mapping function is applied to the HDR image data. A color-compression is applied to the tone mapped image data to generate Standard Dynamic Range or Low Dynamic Range image data.

Abstract: In order to more accurately white balance an image, weightings can be determined for pixels of an image when computing an illuminant color value of the image and/or a scene. The weightings can be based at least in part on the Signal-to-Noise Ratio (SNR) of the pixels. The SNR may be actual SNR or SNR estimated from brightness levels of the pixels. SNR weighting (e.g., SNR adjustment) may reduce the effect of pixels with high noise on the computed illuminant color value. For example, one or more channel values of the illuminant color value can be determined based on the weightings and color values of the pixels. One or more color gain values can be determined based on the one or more channel values of the illuminant color value and used to white balance the image.

Abstract: In various examples, apparatuses, systems, and techniques to perform offline image signal processing of source image data to generate target image data. In at least one embodiment, data collection using exposure and calibration setting of an image sensor is performed to generate source image data, which is then processed by using offline image signal processing to generate target data.

Abstract: Apparatuses, systems, and techniques to perform effective tone management for image data. In an embodiment, a set of contrast gain curves are generated corresponding to a set of tonal ranges of an input image. An output image may then be generated by at least applying corresponding contrast gain curves to tonal ranges of the input image.

Abstract: In order to more accurately white balance an image, weightings can be determined for pixels of an image when computing an illuminant color value of the image and/or a scene. The weightings can be based at least in part on the Signal-to-Noise Ratio (SNR) of the pixels. The SNR may be actual SNR or SNR estimated from brightness levels of the pixels. SNR weighting (e.g., SNR adjustment) may reduce the effect of pixels with high noise on the computed illuminant color value. For example, one or more channel values of the illuminant color value can be determined based on the weightings and color values of the pixels. One or more color gain values can be determined based on the one or more channel values of the illuminant color value and used to white balance the image.

Abstract: An energy storage device includes a phase-change energy storage tank, a first liquid inlet pipe, a first liquid outlet pipe, a second liquid inlet pipe, a second liquid outlet pipe, and a pipeline. The phase-change energy storage tank includes a first housing and a second housing disposed in the first housing. The second housing includes a liquid inlet, a liquid outlet, a feeding hole, and a discharge hole. The first housing includes a thermal insulation material. The second housing includes a phase change material. The liquid inlet and the liquid outlet are disposed on two ends of the second housing, respectively. The phase change material is introduced to and discharged out of the second housing via the feeding hole and the discharge hole, respectively. The first liquid inlet pipe, the phase-change energy storage tank, and the first liquid outlet pipe are connected sequentially to form an energy storage unit.

Abstract: The various embodiments of the present disclosure are directed towards methods for tone mapping High-Dynamic-Range (HDR) image data, as well as controlling the brightness of the image encoded by HDR the image data and/or the tone-mapped image data. HDR image is captured. A tone mapping function for the HDR image data is generated. To generate the tone mapping function, control points are dynamically determined based on an analysis of the HDR image data. The tone mapping function is fit to the control points. The tone mapping function is a non-linear function, and is described by a curve in a plane. The shape of the curve is constrained by a line generated from a portion of the control points. The tone mapping function is applied to the HDR image data. A color-compression is applied to the tone mapped image data to generate Standard Dynamic Range or Low Dynamic Range image data.

Abstract: The various embodiments of the present disclosure are directed towards methods for tone mapping High-Dynamic-Range (HDR) image data, as well as controlling the brightness of the image encoded by HDR the image data and/or the tone-mapped image data. HDR image is captured. A tone mapping function for the HDR image data is generated. To generate the tone mapping function, control points are dynamically determined based on an analysis of the HDR image data. The tone mapping function is fit to the control points. The tone mapping function is a non-linear function, and is described by a curve in a plane. The shape of the curve is constrained by a line generated from a portion of the control points. The tone mapping function is applied to the HDR image data. A color-compression is applied to the tone mapped image data to generate Standard Dynamic Range or Low Dynamic Range image data.

Abstract: An energy storage device includes a phase-change energy storage tank, a first liquid inlet pipe, a first liquid outlet pipe, a second liquid inlet pipe, a second liquid outlet pipe, and a pipeline. The phase-change energy storage tank includes a first housing and a second housing disposed in the first housing. The second housing includes a liquid inlet, a liquid outlet, a feeding hole, and a discharge hole. The first housing includes a thermal insulation material. The second housing includes a phase change material. The liquid inlet and the liquid outlet are disposed on two ends of the second housing, respectively. The phase change material is introduced to and discharged out of the second housing via the feeding hole and the discharge hole, respectively. The first liquid inlet pipe, the phase-change energy storage tank, and the first liquid outlet pipe are connected sequentially to form an energy storage unit.

Abstract: The various embodiments of the present disclosure are directed towards methods for tone mapping High-Dynamic-Range (HDR) image data, as well as controlling the brightness of the image encoded by HDR the image data and/or the tone-mapped image data. HDR image is captured. A tone mapping function for the HDR image data is generated. To generate the tone mapping function, control points are dynamically determined based on an analysis of the HDR image data. The tone mapping function is fit to the control points. The tone mapping function is a non-linear function, and is described by a curve in a plane. The shape of the curve is constrained by a line generated from a portion of the control points. The tone mapping function is applied to the HDR image data. A color-compression is applied to the tone mapped image data to generate Standard Dynamic Range or Low Dynamic Range image data.

Abstract: In order to more accurately white balance an image, weightings can be determined for pixels of an image when computing an illuminant color value of the image and/or a scene. The weightings can be based at least in part on the Signal-to-Noise Ratio (SNR) of the pixels. The SNR may be actual SNR or SNR estimated from brightness levels of the pixels. SNR weighting (e.g., SNR adjustment) may reduce the effect of pixels with high noise on the computed illuminant color value. For example, one or more channel values of the illuminant color value can be determined based on the weightings and color values of the pixels. One or more color gain values can be determined based on the one or more channel values of the illuminant color value and used to white balance the image.