Methods and systems are described for condition mitigation. A computing device may display content. The computing device may determine that displaying and/or outputting the content may impact a person with a condition. The computing device may take an action to reduce an impact of the content on the person.

An image decoding device (31) includes a transform coefficient decoding unit (311) configured to decode a transform coefficient for a transform tree included in a coding unit. In the transform tree, the transform coefficient decoding unit splits a transform unit corresponding to luminance and then decodes the transform coefficient related to the luminance, and does not split the transform unit corresponding to chrominance and decodes the transform coefficient related to the chrominance.

An image decoding device (31) includes a transform coefficient decoding unit (311) configured to decode a transform coefficient for a transform tree included in a coding unit. In the transform tree, the transform coefficient decoding unit splits a transform unit corresponding to luminance and then decodes the transform coefficient related to the luminance, and does not split the transform unit corresponding to chrominance and decodes the transform coefficient related to the chrominance.

Systems, apparatuses and methods may a performance-enhanced computing system comprising a sensor for measuring luminance values corresponding to light focused onto the sensor at a plurality of pixel locations, a memory including a set of instructions, and a processor. The processor executes a set of instructions causing the system to generate a multi-segment tone mapping curve, generate a set of tone mapping values corresponding to the multi-segment tone mapping curve for equally spaced input values between zero and one for storage into a look up table, and process the luminance values using the look up table to apply the tone mapping curve to the luminance values of the pixels.

Systems, apparatuses and methods may a performance-enhanced computing system comprising a sensor for measuring luminance values corresponding to light focused onto the sensor at a plurality of pixel locations, a memory including a set of instructions, and a processor. The processor executes a set of instructions causing the system to generate a multi-segment tone mapping curve, generate a set of tone mapping values corresponding to the multi-segment tone mapping curve for equally spaced input values between zero and one for storage into a look up table, and process the luminance values using the look up table to apply the tone mapping curve to the luminance values of the pixels.

Techniques are described for efficient high-resolution output of an image captured using a high-pixel-count image sensor based on pixel binning followed by luminance-guided umsampling. For example, an image sensor array is configured according to a red-green-blue-luminance (RGBL) CFA pattern, such that at least 50-percent of the imaging pixels of the array are luminance (L) pixels. Pixel binning is used during readout of the array to concurrently generate a downsampled RGB capture frame and a downsampled L capture frame. Following the readout, the L capture frame is upsampled (e.g., by upscaling and interpolation) to generate an L guide frame with 100-percent luminance density. An upsampled RGB frame can then be generated by interpolating the RGB capture frame based both on known neighboring RGB information (e.g., from the RGB capture frame and previously interpolated information), as adjusted based on local luminance information from the L guide frame.

Techniques are described for efficient high-resolution output of an image captured using a high-pixel-count image sensor based on pixel binning followed by luminance-guided umsampling. For example, an image sensor array is configured according to a red-green-blue-luminance (RGBL) CFA pattern, such that at least 50-percent of the imaging pixels of the array are luminance (L) pixels. Pixel binning is used during readout of the array to concurrently generate a downsampled RGB capture frame and a downsampled L capture frame. Following the readout, the L capture frame is upsampled (e.g., by upscaling and interpolation) to generate an L guide frame with 100-percent luminance density. An upsampled RGB frame can then be generated by interpolating the RGB capture frame based both on known neighboring RGB information (e.g., from the RGB capture frame and previously interpolated information), as adjusted based on local luminance information from the L guide frame.

A camera assembly, an image acquisition method, and a mobile terminal are provided. The image acquisition method is applied to a mobile terminal including the camera assembly provided in this disclosure, and the image acquisition method includes: acquiring first image data derived from an exposure of a filtering and photosensitive module in the camera assembly and second image data derived from an exposure of a photosensitive module in the camera assembly; generating a target image from the first image data and the second image data.

In a method for operating a household cooking appliance, a camera records a pixel-based image from a cooking chamber of the household cooking appliance. The image is evaluated with exclusion of brightness values of associated pixels thereof.

In a method for operating a household cooking appliance, a camera records a pixel-based image from a cooking chamber of the household cooking appliance. The image is evaluated with exclusion of brightness values of associated pixels thereof.