A New Method for Superresolution Image Reconstruction Based on Surveying Adjustment

A new method for superresolution image reconstruction based on surveying adjustment method is described in this paper. The main idea of such new method is that a sequence of low-resolution images are taken firstly as observations, and then observation equations are established for the superresolution image reconstruction. The gray function of the object surface can be found by using surveying adjustment method from the observation equations. High-resolution pixel value of the corresponding area can be calculated by using the gray function. The results show that the proposed algorithm converges much faster than that of conventional superresolution image reconstruction method. By using the new method, the visual feeling of reconstructed image can be greatly improved compared to that of iterative back projection algorithm, and its peak signal-to-noise ratio can also be improved by nearly 1 dB higher than the projection onto convex sets algorithm. Furthermore, this method can successfully avoid the ill-posed problems in reconstruction process

A Review of Teacher Transformational Leadership in Higher Education: The Fourth Wave of Teacher Leadership

Transformational leadership offers world-wide scholars a new paradigm to leadership research, and it occupies a central place in leadership research and is rendered as a crucial indicator of promoting students’ academic outcomes. This literature review sought to provide a general picture of transformational leadership as well as its application in higher education context, through which its readers can have a better understanding of what has been done about the topic and what remains to be done in the future. It can seen that the examination of the existing literature further confirmed the validity and effectiveness of teacher transformational leadership in higher educational settings