The image decoding method includes: determining a context for use in a current block to be processed, from among a plurality of contexts; and performing arithmetic decoding on a bit sequence corresponding to the current block, using the determined context, wherein in the determining: the context is determined under a condition that control parameters of neighboring blocks of the current block are used, when the signal type is a first type, the neighboring blocks being a left block and an upper block of the current block; and the context is determined under a condition that the control parameter of the upper block is not used, when the signal type is a second type, and the second type is one of “ref_idx_l0” and “ref_idx_l1”.

A method including automatically segmenting regions of images of a focal stack into segment regions; and based, at least partially, upon selection of one or more of the segment regions, generating a refocused image which induces different ones of the segment regions from at least two of the images of the focal stack. An apparatus including an image segmentator for a focal stack of images, where the image segmentator is configured to automatically form segment regions for each of the images; and a focal stack fuser configured to fuse the focal stack of images into a refocused image, where the refocused image comprises different ones of the segment regions from at least two of the images of the focal stack.

According to one embodiment, an image processing apparatus includes an encoding unit that compresses an input image for each pixel block having a size smaller than a line to generate a plurality of compressed blocks, and store the compressed blocks in a frame buffer, a reading unit that identifies an object block to be expanded among the compressed blocks, and reads the object block from the frame buffer, a decoding unit that expands the object block to generate an expanded block, and an information acquiring unit that acquires, based on the expanded block, position information used by the reading unit to identify the block to be expanded, or decode information used by the decoding unit to expand another compressed block.

Methods, apparatuses and systems may provide for operating a machine learning device by obtaining training image data, conducting an offline prediction analysis of the training image data with respect to one or more real-time parameters of an image capture device, and generating one or more parameter detection models based on the offline prediction analysis. Additionally, methods, apparatuses and systems may provide for operating the image capture device by obtaining a candidate image associated with the image capture device, determining that the candidate image corresponds to a particular type of scene represented in a parameter prediction model, and adjusting one or more real-time parameters of the image capture device based at least in part on one or more parameter values associated with the particular type of scene.

Methods and apparatuses for capturing images used for generating three-dimensional (3D) models of rooms are described herein. User location indicators and image location indicators are displayed on a display of a mobile computing device, such as, but not limited to, a smartphone, a tablet computing device, or a laptop computer. Images and corresponding orientation information are obtained for each of a plurality of walls of each of a plurality of rooms using a camera and at least one sensor of the mobile computing device. The obtained images and corresponding orientation information are transferred from the mobile computing device to a remote system that is configured to generate 3D models of rooms based on images. The mobile computing device receives data that enables the mobile computing device to display a 3D model of the room(s) that was/were imaged.

Provided in an example is a method of compressing a digital image includes dividing the image into cells of constant physical size regardless of resolution of the image to produce cell data for each cell which defines content of the cell and compressing the cell data.

An image coding method in which a chroma component and a luma component of an input image including one or more transform blocks are transformed to code the input image. The luma component has the same size as the current transform block. The chroma component is smaller than the current transform block. In the method, when the current transform block has a first minimum size, the chroma component is transformed on a basis of a block resulting from binding a plurality of the chroma blocks to has the same size as the luma block, and when the current transform block has a size other than the first minimum size, a CBF flag indicating whether or not coefficients of the chroma component include a non-zero coefficient is not coded.

A diagnosis support device, which is suitable for comparing different diseases, is provided, along with others. In the diagnosis support device, the input of an MRI brain image of a subject is received, and a shrinkage score, which represents the degree of shrinkage of the brain, is calculated based on the MRI brain image. Subsequently, sites to be compared in the brain are identified. Then, a degree of shrinkage, which represents the degree of shrinkage of each of the identified sites, and a shrinkage ratio, which is the ratio between the degrees of shrinkage of the sites, are calculated, and then compared and displayed.

A facility for initiating a purchase is described. The facility receives a text sequence captured by a user from a rendered document using a handheld text capture device. The facility identifies in the received text sequence a reference to a distinguished product. In response to identifying the reference, the facility presents to the user an opportunity to place an order for the established product. If the user accepts the presented opportunity to order the distinct product, the facility orders the distinct product on behalf of the user.

Methods and apparatus are provided for determining quantization parameter predictors from a plurality of neighboring quantization parameters. An apparatus includes an encoder for encoding image data for at least a portion of a picture using a quantization parameter predictor for a current quantization parameter to be applied to the image data. The quantization parameter predictor is determined using multiple quantization parameters from previously coded neighboring portions. A difference between the current quantization parameter and the quantization parameter predictor is encoded for signaling to a corresponding decoder.