Abstract: A system on chip and method for operating a system on chip are provided. A system on chip includes a shared memory configured to store image data and a processor configured to: generate a first correction value by performing first image processing for a first pixel value of a first pixel of the image data received from the shared memory, generate a second correction value by performing second image processing, which is different from the first image processing, for the first pixel value of the image data received from the shared memory, generate a third correction value by performing third image processing, which is different from the first image processing and the second image processing, for the first pixel value of the image data received from the shared memory, and output a first pixel correction value that is changed from the first pixel value by comparing the first to third correction values with the first pixel value and selecting one of the first to third correction values.

Abstract: Provided is a method of estimating a dynamic coefficient of an electric vehicle and predicting energy consumption by utilizing speed log data and a physics-informed neural network enabling derivation of a physics-informed neural network for predicting a dynamic parameter and accurate prediction of instantaneous battery power and cumulative energy consumption based thereon including collecting log data for predicting energy consumption of the electric vehicle in a processor for predicting energy consumption of the electric vehicle using a model including a physics-informed neural network, deriving a dynamic model for predicting battery power dynamics of the electric vehicle, setting a loss function of the derived dynamic model, training and optimizing an energy consumption measurement model, which is a physics-informed neural network generated based on the set loss function, and predicting cumulative energy consumption using the energy consumption measurement model, which is the optimized physics-informed neur

Abstract: There is provide an image encoding method including transforming an image block into a first latent representation based on an invertible neural network, transforming the first latent representation into a second latent representation based on a non-invertible neural network, estimating a probability distribution of the first latent representation, and performing entropy encoding on the first latent representation based on the probability distribution by using an entropy encoder.

Abstract: A video encoder is provided. The video encoder according to an example embodiment includes: a differentiable prediction (DP) module configured to output an optimal initial search position by performing full search in a predetermined area by using a pair of frames of a video as input; and a motion estimation (ME) module configured to perform motion estimation by moving a search position toward the optimal initial search position output by the DP module.

Abstract: An image encoding apparatus may include a memory storing one or more instructions; and a processor configured to execute the one or more instructions to: obtain an initial search position from a student neural network that has been trained through a knowledge distillation from a teacher neural network by inputting a current frame and a reference frame to the student neural network; and perform motion estimation based on the initial search position.

Abstract: A system on chip includes: a codec encoding image frames; and a codec controller sending the image frames to the codec and allocating a buffer for encoding the image frames. The codec controller sends a first image frame to the codec. The codec controller allocates the first buffer to a memory and sends the first image frame to the codec. The codec encodes the first image frame and sends the encoded first image frame to the codec controller. The codec controller allocates the first buffer to the memory and sends a second image frame to the codec. The codec requests the codec controller to allocate a second buffer of a second size. The codec controller allocates the second buffer to the memory and sends the second image frame to the codec, and the codec encodes the second image frame and sends the encoded second image frame to the codec controller.

Abstract: A system on chip includes: a codec encoding image frames; and a codec controller sending the image frames to the codec and allocating a buffer for encoding the image frames, The codec controller sends a first image frame to the codec. The codec controller allocates the first buffer to a memory and sends the first image frame to the codec. The codec encodes the first image frame and sends the encoded first image frame to the codec controller. The codec controller allocates the first buffer to the memory and sends a second image frame to the codec. The codec requests the codec controller to allocate a second buffer of a second size. The codec controller allocates the second buffer to the memory and sends the second image frame to the codec, and the codec encodes the second image frame and sends the encoded second image frame to the codec controller.

Abstract: A video encoder is provided. The video encoder according to an example embodiment includes: a differentiable prediction (DP) module configured to output an optimal initial search position by performing full search in a predetermined area by using a pair of frames of a video as input; and a motion estimation (ME) module configured to perform motion estimation by moving a search position toward the optimal initial search position output by the DP module.

Abstract: An image encoding apparatus may include a memory storing one or more instructions; and a processor configured to execute the one or more instructions to: obtain an initial search position from a student neural network that has been trained through a knowledge distillation from a teacher neural network by inputting a current frame and a reference frame to the student neural network; and perform motion estimation based on the initial search position.

Abstract: There is provide an image encoding method including transforming an image block into a first latent representation based on an invertible neural network, transforming the first latent representation into a second latent representation based on a non-invertible neural network, estimating a probability distribution of the first latent representation, and performing entropy encoding on the first latent representation based on the probability distribution by using an entropy encoder.

Abstract: An image signal processor includes a statistic data generating unit for receiving an image signal from an external device, an image processing unit for receiving the image signal, and a direct memory access (DMA) module connected to the statistic data generating unit and the image processing unit. The statistic data generating unit performs first image pre-processing on the image signal and generates first statistic data based on the image signal subjected to the first image pre-processing. The DMA module stores the first statistic data therein and provides the stored first statistic data to the image processing unit. The image processing unit performs second image pre-processing on the image signal and performs image processing on the image signal based on the first statistic data.

Abstract: A system on chip and method for operating a system on chip are provided. A system on chip includes a shared memory configured to store image data and a processor configured to: generate a first correction value by performing first image processing for a first pixel value of a first pixel of the image data received from the shared memory, generate a second correction value by performing second image processing, which is different from the first image processing, for the first pixel value of the image data received from the shared memory, generate a third correction value by performing third image processing, which is different from the first image processing and the second image processing, for the first pixel value of the image data received from the shared memory, and output a first pixel correction value that is changed from the first pixel value by comparing the first to third correction values with the first pixel value and selecting one of the first to third correction values.

Abstract: An image signal processor includes a statistic data generating unit for receiving an image signal from an external device, an image processing unit for receiving the image signal, and a direct memory access (DMA) module connected to the statistic data generating unit and the image processing unit. The statistic data generating unit performs first image pre-processing on the image signal and generates first statistic data based on the image signal subjected to the first image pre-processing. The DMA module stores the first statistic data therein and provides the stored first statistic data to the image processing unit. The image processing unit performs second image pre-processing on the image signal and performs image processing on the image signal based on the first statistic data.

Abstract: A circuit for driving a liquid crystal display device includes a liquid crystal panel including a plurality of gate lines and data lines, a gate driver, a data driver, a memory for storing data necessary for operation of a timing controller and programmable power integrated circuit (PPIC) voltage setting data, the timing controller for reading and outputting the PPIC voltage setting data stored in the memory and reading the data necessary for operation of the timing controller stored in the memory and controlling the data driver and the gate driver, a PPIC for supplying a reference voltage, a gamma voltage and a common voltage to the data driver according to the voltage setting data supplied by the timing controller, and a power supply for receiving power from an external device and supplying power to each unit.

Abstract: A display module including a touch panel configured to be touched so as to input information, a liquid crystal display panel disposed below the touch panel and configured to display the information to be touched on the touch panel, a plurality of emitting light units configured to emit infrared light formed in at least two sides of the touch panel, a plurality of image sensors disposed below the liquid crystal panel and configured to detect infrared rays redirected through the liquid crystal panel towards the image sensors based on a touching of the touch panel, and a controller configured to determine a portion of the touch panel that is touched based on signals received from the plurality of image sensors.

Abstract: A method of controlling a stereo vision device includes calculating depth information by analyzing stereo images, setting regions of interest within each of the stereo images by using the depth information, and performing an auto focus operation on each of the regions of interest. The method may further include performing an auto exposure operation on each of the regions of interest.

Abstract: A touch panel display device includes a liquid crystal panel to display an image by regulating transmittance of light supplied from a back light unit, and a touch sensing part provided on upper edges of the liquid crystal panel in order to detect a position touched by a user or an object. The touch sensing part includes infrared lamps to generate and emit infrared light, infrared light reflecting tubes mounted with the infrared lamps, and image sensors to sense the infrared light output from the light output regions of the infrared light reflecting tubes. Each of the infrared light reflecting tubes has light output regions and non-output regions evenly formed at a surface facing an upper surface of the liquid crystal panel so that the infrared light emitted from the infrared lamps is evenly irradiated on the upper surface of the liquid crystal panel.

Abstract: Provided are a multi-touch system and a driving method thereof. The method includes, extracting using a digital processor a touch frequency and at least one angle associated with at least one touch from image information captured by each of at least two cameras, selecting a touch mode on the basis of sum value of the touch frequencies extracted from the image information captured by the cameras, and performing a touch function corresponding to the selected touch mode using a user interface.

Abstract: A display device capable of simplifying the structure and improving the reliability is disclosed. The display device includes an LCD module having a top case formed of metal, a glass substrate arranged on the LCD module, an infrared ray emitting module arranged to face three side surfaces of the LCD module and having a first magnet for first fixing to the top case, and a pair of infrared ray detection units arranged at corner ends of a side surface of the LCD module where the infrared ray emitting module is not arranged and having a second magnet for the first fixing to the top case.

Abstract: A dynamic range enhancement method and apparatus for an imaging device expands a dynamic range of an input image without an associated increase in the amount of image calculations. The dynamic range enhancement method includes producing brightness information and color information from an input image; applying gamma correction and inverse gamma correction to the brightness information to produce a gamma corrected image and an inverse gamma corrected image; comparing variances of the gamma corrected image and the inverse gamma corrected image at identical spots; and expanding a dynamic range of the input image by selecting one of the variances at each spot. The dynamic range of an input image is expanded by applying a post imaging process without increasing calculation amount of the imaging device.