Computer processor hardware receives a first set of adjustment values. The first set of adjustment values specify adjustments to be made to a predicted rendition of a signal generated at a first level of quality to reconstruct a rendition of the signal at the first level of quality. The computer processor hardware processes the first set of adjustment values and derives a second set of adjustment values based on the first set of adjustment values and a rendition of the signal at a second level of quality. The second level of quality is lower than the first level of quality.

Computer processor hardware receives a first set of adjustment values. The first set of adjustment values specify adjustments to be made to a predicted rendition of a signal generated at a first level of quality to reconstruct a rendition of the signal at the first level of quality. The computer processor hardware processes the first set of adjustment values and derives a second set of adjustment values based on the first set of adjustment values and a rendition of the signal at a second level of quality. The second level of quality is lower than the first level of quality.

In the video processing device, the video acquisition means acquires a material video. The audience scene extraction means extracts an audience scene showing an audience from the material video. The important scene extraction means extracts an important scene from the material video. The association means associates the audience scene with the important scene. The generation means generates a digest video including the important scene and the audience scene associated with the important scene.

In the video processing device, the video acquisition means acquires a material video. The audience scene extraction means extracts an audience scene showing an audience from the material video. The important scene extraction means extracts an important scene from the material video. The association means associates the audience scene with the important scene. The generation means generates a digest video including the important scene and the audience scene associated with the important scene.

Computer processor hardware receives image data specifying element settings for each image of multiple original images in a sequence. The computer processor hardware analyzes the element settings across the multiple original images. The computer processor hardware then utilizes the element settings of the multiple original images in the sequence to produce first encoded image data specifying a set of common image element settings, the set of common image element settings being a baseline to substantially reproduce each of the original images in the sequence.

Computer processor hardware receives image data specifying element settings for each image of multiple original images in a sequence. The computer processor hardware analyzes the element settings across the multiple original images. The computer processor hardware then utilizes the element settings of the multiple original images in the sequence to produce first encoded image data specifying a set of common image element settings, the set of common image element settings being a baseline to substantially reproduce each of the original images in the sequence.

Video and corresponding metadata is accessed. Events of interest within the video are identified based on the corresponding metadata, and best scenes are identified based on the identified events of interest. Events of interest can be tagged within the video based on, for instance, user input, audio signals, motion vectors, and metadata corresponding to the video. A camera system can process video data based on the events of interest tagged within the video before outputting the video data. For instance, video scenes associated with tagged events of interest can be combined to form a video highlight clip. Likewise, portions of video tagged with events of interest can be encoded or stored at a higher resolution or frame rate than other portions of the video.

Video and corresponding metadata is accessed. Events of interest within the video are identified based on the corresponding metadata, and best scenes are identified based on the identified events of interest. Events of interest can be tagged within the video based on, for instance, user input, audio signals, motion vectors, and metadata corresponding to the video. A camera system can process video data based on the events of interest tagged within the video before outputting the video data. For instance, video scenes associated with tagged events of interest can be combined to form a video highlight clip. Likewise, portions of video tagged with events of interest can be encoded or stored at a higher resolution or frame rate than other portions of the video.

A method for enhancing at least a section of lower-quality visual data using a hierarchical algorithm, the method comprising receiving at least a plurality of neighbouring sections of lower-quality visual data. A plurality of input sections from the received plurality of neighbouring sections of lower quality visual data are selected and features are extracted from those plurality of input sections of lower-quality visual data. A target section based on the extracted features from the plurality of input sections of lower-quality visual data is then enhanced.

There is provided an image archiving method for use with a writing target, comprising the steps of receiving a series of captured images of the writing target, detecting difference between first and second candidate received images separated by a predetermined period of time, where additive differences are indicative of writing and subtractive differences are indicative of erasure; upon detecting subtractive difference, temporarily retaining a last candidate image captured prior to the detection, and detecting whether the subtractive difference relative to the retained image exceeds a subtraction threshold amount; and if so, then storing the retained image.