Abstract: In this paper a new method for Full Reference Image Quality Assessment is presented. In current work the edge of the image is analyzed and the best scenario about the color is found. In first step the RGB, HSI and YCbCr color aretested. For each color the wavelet transform is applied and the edge of the images are extracted. With edge intensity specification the image quality assessment is tested. As result shown in this paper the PSNR, SROCC and Pearson is calculated. 

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The segmentation of various retinal layers is vital for diagnosing and tracking progress of medication of various ocular diseases. Due to the complexity of retinal structures, the tediousness of manual segmentation and variation from different specialists, many methods have been proposed to aid with this analysis. However image artifacts, in addition to inhomogeneity in pathological structures, remain a challenge, with negative influence on the performance of segmentation algorithms. Previous attempts normally pre-process the images or model the segmentation to handle the obstruction but it still remains an area of active research, especially in relation to the graph based algorithms. In this paper we present an automatic retinal layer segmentation method, which is comprised of fuzzy histogram hyperbolization and graph cut methods to segment 8 boundaries and 7 layers of the retina on 150 OCT B-Sans images, 50 each from the temporal, nasal and centre of foveal region. Our method shows positive results, with additional tolerance and adaptability to contour variance and pathological inconsistency of the retinal structures in all regions.

Melt electrospinning is a technique capable of producing micro-and nanofibers with the advantages of being eco-friendly, cost-effective, and applied in many areas such as nonwovens with high performance, biomedicine, high-efficiency filtration, oil sorption, and many others. This chapter describes the current trends on melt electrospinning including advancements in the technique, processing parameters, materials, apparatus, and areas of applications. Melt differential electrospinning which is a new technique for nanofiber production invented by our innovation team of advanced polymer processing has been introduced. Future perspectives on melt electrospinning are also proposed.

Polyphenylene sulfide (PPS) superfine fiber is a promising high efficient material for high temperature dedusting. In this paper, the PPS superfine fiber was prepared by melt-electrospinning for the first time. In order to produce the finer fibers, the polypropylene (PP) was added to PPS and the effects of blending ratio, spinning voltage, spinning temperature, and spinning distance on resultant fibers were investigated systematically. The superfine fibers of PPS with an average diameter of 4.12 μm were successfully prepared at the optimized condition, which was one third of that by melt-spinning method. With the decrease of 76.21 % fibers diameter, the filter efficiency increased from 87.03 % to 98.05 %. The presented method provides a new way for the scalable and green fabrication of PPS superfine fibers.