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TUTCRIS

Structural Similarity Index with Predictability of Image Blocks

Tutkimustuotosvertaisarvioitu

Yksityiskohdat

AlkuperäiskieliEnglanti
Otsikko2018 IEEE 17th International Conference on Mathematical Methods in Electromagnetic Theory, MMET 2018 - Proceedings
KustantajaIEEE COMPUTER SOCIETY PRESS
Sivut115-118
Sivumäärä4
Vuosikerta2018-July
ISBN (painettu)9781538654385
DOI - pysyväislinkit
TilaJulkaistu - 10 syyskuuta 2018
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaIEEE International Conference on Mathematical Methods in Electromagnetic Theory - Kyiv, Ukraina
Kesto: 2 heinäkuuta 20185 heinäkuuta 2018

Julkaisusarja

Nimi
ISSN (elektroninen)2161-1750

Conference

ConferenceIEEE International Conference on Mathematical Methods in Electromagnetic Theory
MaaUkraina
KaupunkiKyiv
Ajanjakso2/07/185/07/18

Tiivistelmä

Structural similarity index (SSIM) is a widely used full-reference metric for assessment of visual quality of images and remote sensing data. It is calculated in a block-wise manner and is based on multiplication of three components: similarity of means of image blocks, similarity of contrasts and a correlation factor. In this paper, two modifications of SSIM are proposed. First, a fourth multiplicative component is introduced to SSIM (thus obtaining SSIM4) that describes a similarity of predictability of image blocks. A predictability for a given block is calculated as a minimal value of mean square error between the considered block and the neighboring blocks. Second, a simple scheme for calculating the metrics SSIM and SSIM4 for color images is proposed and optimized. Effectiveness of the proposed modifications is confirmed for the specialized image databases TID2013, LIVE, and FLT. In particular, the Spearman rank order correlation coefficient (SROCC) for the recently introduced FLT Database, calculated between the proposed metric color SSIM4 and mean opinion scores (MOS), has reached the value 0.85 (the best result for all compared metrics) whilst for SSIM it is equal to 0.58.