Multiple Description Image Coding with Local Random Measurements
In this paper, an effective multiple description image coding technique is developed to achieve competitive coding efficiency at low encoder complexity, while being standard compliant. The new technique is particularly suitable for visual communication over packet-switched networks and with resource-deficient wireless devices. To keep the encoder simple and standard compliant, multiple descriptions are produced by quincunx spatial multiplexing. Each side description is a polyphase down sampled version of the input image, but the conventional low-pass filter prior to downsampling is replaced by a local random binary convolution kernel. The pixels of each resulting side description are local random measurements and placed in the original spatial configuration. The advantages of local random measurements are two folds: 1) preservation of high-frequency image features that are otherwise discarded by low-pass filtering, 2) each side description remains a conventional image and can therefore be coded by any standardized codec to remove statistical redundancy of larger scales. The decoder performs joint upsampling of received description(s) and recovers the image from local random measurements in a framework of compressive sensing. Experimental results demonstrate that the proposed multiple description image codec is competitive in rate-distortion performance compared with existing methods, with a unique strength of recovering fine details and sharp edges at low bit rates.