1. Field of the Invention
The present invention relates to image data filtering.
2. Background Art
An increasing number of devices are being produced that are enabled to capture and display images. For example, mobile devices, such as cell phones, are increasingly being equipped with cameras to capture images, including still snapshots and motion video images. Images captured by such devices can frequently be viewed on displays of the devices, as well as being transferred from the devices for viewing elsewhere. To view the images on relatively small devices, the images typically must be viewed on small display screens that are not capable of viewing the full resolution of the captured images. Thus, such devices must include at least limited image processing capability to down-size the images for viewing on the small display screens.
Many mobile devices have limited processing capability due to cost, power consumption, and size constraints. However, the processing of captured images, especially the processing of video, is very computationally intensive. For example, many mobile devices have cameras capable of capturing images of 2 MegaPixels (MPel) or more. Thus, a processor of such a mobile device must be capable of processing a large amount of data for each captured image. Furthermore, encoding and decoding (e.g., QCIF) of image data may need to be performed by the processor at frame rates such as 15 fps and 30 fps, respectively, as well as the performance of other functions.
To deal with such high-resource demanding tasks, mobile device developers have resorted to including high-powered processing chips in the devices, which have higher clock rates and larger on-chip cache memory, or to including dedicated video/image processing chips. Such approaches result in higher cost devices with higher levels of power consumption, which may not be desirable in battery powered mobile devices.
Thus, ways are desired for handling an image processing workload in devices, such as mobile devices, without significantly raising device costs and power consumption levels.