Abstract
An image is compressed to reduce the memory or bandwidth it occupies. Compression is presently carried out such that the reconstructed (decompressed) image is faithful to the original image. In some recent contexts, images are generated that are not necessarily intended for human viewership. For example, such images are generated for the purposes of machine-based tasks such as action-detection, scene-recognition, etc. In such cases, compression that is driven by fidelity of the decompressed image to the original can be sub-optimal. This disclosure describes techniques to compress images based on the end use of the image. For example, if an image is used for the purposes of detecting particular objects within it, then image compression is driven by an object detector. Portions of the image that are irrelevant to detecting the sought objects are excised during compression. The result is a more efficient, task-specific, encoding of the image.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Baluja, Shumeet; Marwood, David; and Johnston, Nicholas, "Task-specific color spaces and compression for machine-based object recognition", Technical Disclosure Commons, (March 21, 2019)
https://www.tdcommons.org/dpubs_series/2067