A novel optimal seam method which aims to stitch those images with overlapping area more seamlessly has been propos ed. Considering the traditional gradient domain optimal seam method and fusion algorithm result in bad color difference measurement and taking a long time respectively, the input images would be converted to HSV space and a new energy function is designed to seek optimal stitching path. To smooth the optimal stitching path, a simplified pixel correction and weighted average method are utilized individually. The proposed methods exhibit performance in eliminating the stitching seam compared with the traditional gradient optimal seam and high efficiency with multi-band blending algorithm.
Interlace is part of television standards since the very start of TV-broadcast. The advent of new display principles that cannot handle interlaced video, the wish to up-scale standard definition video for display on large high-definition screens and the introduction of video in traditionally non-interlaced multimedia PCs ask for advanced de-interlacing techniques.
Various de-interlacing techniques can be categorized into non-motion compensated methods and motion compensated methods. The former includes linear techniques such as spatial filtering, temporal filtering, vertical-temporal filtering and non-linear techniques like motion adaptive filtering, edge-dependent interpolation, implicitly adapting methods and hybrid methods. The latter category includes temporal backward projection, time-recursive de-interlacing, adaptive-recursive de-interlacing, generalized sampling theorem de-interlacing method and hybrid method. An objective comparison based on Mean Square Error (MSE) and Motion Trajectory Inconsistency (MTI) metric has been given on above listed methods. In this paper, we describe a subjective assessment in which a number of de-interlacing techniques will be ranked by a group of viewers (typically twenty persons). The experiment was set-up according to the recommendations of the ITU. Combined with the objective scores presented in the earlier publications, we then have a thorough analysis of each selected de-interlacing algorithms. This improves the relevance and reliability of our knowledge concerning the performance of these de-interlacing algorithms.
In a Standard Definition (SD) Television system, the Y:U:V video format 4:2:2 with chrominance sub-sampling is widely used. With the advent of High Definition (HD) television, the 4:4:4 format is required for high-performance TV. High-quality up-sampling methods have been developed to perform a resolution conversion from Standard Definition (SD) signal to HD signal. Although these algorithms have been designed for spatial scaling of luminance, they may be adapted and used to up-sample the low-resolution components U,V (4:2:2) to a high-resolution UV-colour format (4:4:4). In this paper, a content-adaptive up-scaling method for chrominance is proposed, with interpolation filters that adapt to the local structure of both luminance and chrominance data. Optimal filters were computed from a large video data set in different colour formats, such that original high-resolution data in a 4:4:4 format was reconstructed from low-resolution colour data, on the basis of the Least Mean Square (LMS) criterion. By combining edge information of both luminance and chrominance, the edge in the chrominance signal can be detected more accurately, thus exploiting the wider bandwidth of the luminance signal.
The introduction of HDTV asks for spatial up-conversion techniques enabling the display of standard resolution material. Recently, X. Li and M. Orchard proposed the 'New Edge-Directed Interpolation' (NEDI) algorithm for high quality up-scaling of natural images. We shall show that the method, although it generally behaves well, introduces annoying artifacts in fine-textured areas. Based on an analysis of these artifacts and taking advantage of the temporal correlation between video images, we propose an improved NEDI algorithm. In our evaluation, we compare the performance of the original and the improved NEDI method on a significant set of test images. We conclude from both subjective and objective measures that the proposed modifications improve the overall performance of NEDI.