This research proposes a novel data assisted image transmission scheme, which utilizes a large amount of correlated images stored in the cloud to improve the spectrum efficiency and visual quality. First, a two-layer Coset coding is proposed for the DCT coefficients transmission. The most significant bits (MSB) of the coefficients are generated by the first layer Coset and together with a few low frequency coefficients are transmitted through the most reliable channel coding and digital modulation. The middle bits generated by the second layer Coset are discarded by the sender and the residual bits are transmitted through amplitude modulation. Based on the MSB and the residual bits, an approximation of the original image is reconstructed. With this approximation, a lot of correlated images can be retrieved from the cloud, which are used to recover the discarded middle bits. The two layer Coset coding can significantly decrease the data energy so as to improve the transmission power efficiency. Hence, the end to end distortion of amplitude modulation can be reduced. Second, the image quality can be further improved by joint internal and external denoising with the retrieved images. Simulations show that the proposed scheme outperforms conventional digital schemes about 4 dB in peak signal to noise power ratio (PSNR) and achieves 2 dB gain over the state-of-the-art uncoded transmission. At low signal to noise power ratio (SNR), an additional 2-3 dB gain is achieved. The visual quality comparison also validates the objective image assessment result.<\/p>\n","protected":false},"excerpt":{"rendered":"
This research proposes a novel data assisted image transmission scheme, which utilizes a large amount of correlated images stored in the cloud to improve the spectrum efficiency and visual quality. First, a two-layer Coset coding is proposed for the DCT coefficients transmission. The most significant bits (MSB) of the coefficients are generated by the first […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13551],"msr-publication-type":[193715],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-374519","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-graphics-and-multimedia","msr-locale-en_us"],"msr_publishername":"IEEE","msr_edition":"IEEE Transactions on Multimedia ( Volume: 18, Issue: 5, May 2016 )","msr_affiliation":"","msr_published_date":"2016-02-29","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"893-904","msr_chapter":"","msr_isbn":"","msr_journal":"IEEE Transactions on Multimedia","msr_volume":"18","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"5","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"","msr_publicationurl":"http:\/\/ieeexplore.ieee.org\/document\/7422133\/","msr_doi":"10.1109\/TMM.2016.2535727","msr_publication_uploader":[{"type":"url","title":"http:\/\/ieeexplore.ieee.org\/document\/7422133\/","viewUrl":false,"id":false,"label_id":0},{"type":"doi","title":"10.1109\/TMM.2016.2535727","viewUrl":false,"id":false,"label_id":0}],"msr_related_uploader":"","msr_attachments":[{"id":0,"url":"http:\/\/ieeexplore.ieee.org\/document\/7422133\/"}],"msr-author-ordering":[{"type":"text","value":"Jun Wu","user_id":0,"rest_url":false},{"type":"text","value":"Jian Wu","user_id":0,"rest_url":false},{"type":"text","value":"Hao Cui","user_id":0,"rest_url":false},{"type":"user_nicename","value":"cluo","user_id":31450,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=cluo"},{"type":"user_nicename","value":"xysun","user_id":34946,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=xysun"},{"type":"text","value":"Feng Wu","user_id":0,"rest_url":false}],"msr_impact_theme":[],"msr_research_lab":[199560],"msr_event":[],"msr_group":[144711],"msr_project":[],"publication":[],"video":[],"download":[],"msr_publication_type":"article","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/374519"}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-research-item"}],"version-history":[{"count":1,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/374519\/revisions"}],"predecessor-version":[{"id":413924,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/374519\/revisions\/413924"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=374519"}],"wp:term":[{"taxonomy":"msr-content-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-content-type?post=374519"},{"taxonomy":"msr-research-highlight","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-highlight?post=374519"},{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=374519"},{"taxonomy":"msr-publication-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-publication-type?post=374519"},{"taxonomy":"msr-product-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-product-type?post=374519"},{"taxonomy":"msr-focus-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-focus-area?post=374519"},{"taxonomy":"msr-platform","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-platform?post=374519"},{"taxonomy":"msr-download-source","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-download-source?post=374519"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=374519"},{"taxonomy":"msr-field-of-study","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-field-of-study?post=374519"},{"taxonomy":"msr-conference","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-conference?post=374519"},{"taxonomy":"msr-journal","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-journal?post=374519"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=374519"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=374519"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}