Apple Inc.

Canon Kabushiki Kaisha

Cisco Technology, Inc.

Olagappan Manickam

Thomas M Alsina

Sean Boland Kelly

Payam Mirrashidi

Michael Kuohao Chu

Kevin R Lafferty

Christopher B Chang

Harry T Garland

Radovan V Krtolica

Alok Batra

Rajendra Kulkarni

Chetan Gadgil

Jonathan E DeVito

Danko Zlokapa

Improved techniques and systems for delivery and acquisition of digital assets are disclosed. The techniques and systems are especially suitable and useful for delivering digital assets (e.g., media assets) that are available for acquisition and electronic delivery from online stores to electronic devices. In accordance with one aspect, when a digital asset is acquired from an online store via an electronic device associated with a user, the digital asset can be arranged for delivery to a number of other of electronic devices also associated with the user. It will be appreciated that the digital asset can be delivered and acquired without requiring explicit user input or instruction in accordance with another aspect. Other aspects of the techniques and systems include customization of configuration and user interfaces that are provided to facilitate acquisition of digital assets in a more efficient manner.

Intelligent delivery and acquisition of digital assets

Improved techniques and systems for delivery and acquisition of digital assets are disclosed. The techniques and systems are especially suitable and useful for delivering digital assets (e.g., media assets) that are available for acquisition and electronic delivery from online stores to electronic devices. In accordance with one aspect, when a digital asset is acquired form an online store via an electronic device associated with a user, the digital asset can be arranged for delivery to a number of other of electronic devices also associated with the user. It will be appreciated that the digital asset can be delivered and acquired without requiring explicit user input or instruction in accordance with another aspect. Other aspects of the techniques and systems include customization of configuration and user interfaces that are provided to facilitate acquisition of digital assets in a more efficient manner.

Separate executable agents each perform tasks on associated information that is changing over time, to produce current information, Inputs and outputs are delivered among agents to enable assembly of a body of aggregated and summarized management information, based on the current information, to be used to manage at least a portion of an enterprise.

Providing enterprise information

Regions of a source image (900) are encoded at different levels of image quality. A plurality of image quality levels are defined (1010). In addition, the source image (900) is divided into one or more regions (912, 914, 916) and one of the image quality levels is assigned to each region (1012). Next, the entire source image (900) is encoded, preferably with JPEG encoding, at the lowest image quality level Q.sub.1, assigned to the image (1016). Then, the encoded source image (900) is decoded by a matching decoding process into a reference frame (1018). If the next highest image quality level Q.sub.2 is lossy, then the reference frame and source image are scaled according to the image quality level Q.sub.2 (1020). Then, differences between the source image and the reference frame are determined for all lossy regions assigned an image quality level greater than or equal to the image quality level Q.sub.2, and stored in a differential frame (1024). The differential frame is encoded according to the image quality level Q.sub.2 (1026), stored with the reference frame, then decoded to become the new reference frame (1028). These steps are repeated until the highest quality level assigned to a region is encoded. If the image quality level is lossless, then the reference frame is scaled to the resolution of the source image (1030), and the differential components are losslessy encoded (1038). When the variably encoded image is decoded, each of the selected regions (912, 914, 916) has the image quality defined by the assigned image quality level.

Variable compression encoding of digitized images

An image scaling system that enlarges images during JPEG encoding (400) and reduces images during JPEG decoding (500). The image scaling system uses N-point forward and inverse one-dimensionial scaled discrete cosine transforms (DCTs), where N is selected from among 1, 2, 3, 4, and 6. When encoding a source image (110) to an enlarged JPEG image (422), the system partitions the source image into N.times.N blocks. Each N.times.N block is transformed using the N-point scaled DCT (410). The system modifies quantization tables (418) to account for the scale of the transform and the increase in size of the image and quantizes (412) the blocks of N.times.N scaled cosine coefficients using the modified quantization tables. The resulting N.times.N blocks are enlarged (414) to 8.times.8 blocks by padding each block with coefficients having values of zero. When decoding a JPEG image (510) to a reduced output image (518), the system retrieves 8.times.8 blocks of quantized cosine coefficients from the JPEG image. The system reduces (512) each block to an N.times.N block of quantized cosine coefficients. The system modifies the quantization tables (520) retrieved from the JPEG image to account for the scale factor and the decrease in size of the image, then quantizes (514) the N.times.N blocks to produce N.times.N blocks of scaled cosine coefficients. The system performs an N-point scaled inverse DCT (516) on each block of scaled cosine coefficients. The results of the inverse DCT form the reduced output image (518). The forward and inverse DCTs are performed using efficient processes that require relatively few calculations to achieve the desired result.

Fast scaling of JPEG images

Growing community of inventors

Cupertino, CA, United States of America

Olagappan Manickam