Implementasi Algoritma A Randomized Iterative Improvement dengan Preprocessing Warna Dominan Tile dalam Pembuatan Photomosaic

ABSTRAKSI: Photomosaic adalah gambar yang disusun dari gambar yang lebih kecil yang disebut dengan tile. Ketika photomosaic dilihat dari jarak tertentu, maka akan terlihat gambar yang sesungguhnya dibentuk dari gambar-gambar kecil tadi. Dalam beberapa tahun ini ada berbagai macam metode yang dikembangkan untuk membuat photomosaic. Hambatan di setiap algoritma photomosaic adalah pencarian gambar di database yang besar untuk menemukan gambar yang paling cocok. Pencarian ini biasanya dilakukan secara sekuensial dan sehingga waktu diperlukan untuk melakukan tugas ini cukup lama. Salah satu algoritma untuk mensiasati lamanya pemrosesan photomosaic tersebut ialah A Randomized Iterative Improvement Algorithm. A Randomized Iterative Improvement Algorithm yang awalnya diusulkan oleh Burke Abdullah dan McCollum untuk memecahkan kasus masalah penjadwalan universitas. Lalu algoritma ini diadaptasi oleh Harikrishna Narasimhan dan Sanjeev Satheesh untuk membuat photomosaic. Dengan algoritma ini maka kita dapat mengatur lamanya waktu pemrosesan yaitu dengan cara mengatur berapa banyak iterasi yang dilakukan untuk menghasilkan photomosaic. Untuk meningkat tingkat kesesuaian pemilihan tile dan kecepatan proses photomosaic maka dalam TA ini ditambahkan preprocessing klasifikasi warna dominan tile. Hal ini dimaksudkan agar pencarian tile lebih cepat dan terarah. Selain itu juga dilakukan perbaikan fungsi fitness menggunakan jarak Euclidean RGB dan Y‟UV. Dari hasil pengujian terbukti bahwa preprocessing klasifikasi warna dominan tile membuat proses pembuatan photomosaic lebih cepat. Selain itu didapatkan juga bahwa penggunaan fungsi fitness jarak Euclidean Y‟UV menghasilkan photomosaic yang lebih bagus dibandingkan dengan fungsi fitness semula dan fungsi fitness jarak Euclidean RGB.Kata Kunci : Photomosaic, Algoritma A Randomized Iterative Improvement, warna dominan, tile, fungsi fitness, RGB, Y‟UVABSTRACT: Photomosaic is an image composed of smaller images called tiles. When photomosaic viewed from a certain distance, it will show the real image formed from the little pictures. In recent years, there are various methods developed to create a photomosaic. Barriers in each photomosaic algorithm is the image search in large databases to find the most suitable image. This search is usually carried out sequentially and so the time required to perform this task quite a while. One algorithm to anticipate the duration of processing the photomosaic is A Randomized Iterative Improvement Algorithm. A Randomized Iterative Improvement Algorithm which was originally proposed by Burke and McCollum Abdullah to solve the case of university scheduling problems. Then the algorithm was adapted by Harikrishna Narasimhan and Sanjeev Satheesh to create a photomosaic. With this algorithm then we can set the length of processing time is by way of set how many iterations are performed to produce a photomosaic. To increase the usefulness of tile selection and speed of the photomosaic process in TA was added preprocessing dominant tile color classification. It aims to make searching faster and directional tiles. It also made improvements fitness function using Euclidean distance and Y\u27UV RGB. From the test results proved that the dominant color of tile classification preprocessing makes the process of making photomosaic faster. Also found also that the use of the fitness function of the Euclidean distance Y\u27UV produce photomosaic better than the original fitness function and fitness function of the Euclidean distance of RGB.Keyword: Photomosaic, A Randomized Iterative Improvement Algorithm, dominant color, tile, fitness function, RGB, Y‟U

Self consistent bathymetric mapping from robotic vehicles in the deep ocean

Submitted In partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and Woods Hole Oceanographic Institution June 2005Obtaining accurate and repeatable navigation for robotic vehicles in the deep ocean is difficult and consequently a limiting factor when constructing vehicle-based bathymetric maps. This thesis presents a methodology to produce self-consistent maps and simultaneously improve vehicle position estimation by exploiting accurate local navigation and utilizing terrain relative measurements. It is common for errors in the vehicle position estimate to far exceed the errors associated with the acoustic range sensor. This disparity creates inconsistency when an area is imaged multiple times and causes artifacts that distort map integrity. Our technique utilizes small terrain "submaps" that can be pairwise registered and used to additionally constrain the vehicle position estimates in accordance with actual bottom topography. A delayed state Kalman filter is used to incorporate these sub-map registrations as relative position measurements between previously visited vehicle locations. The archiving of previous positions in a filter state vector allows for continual adjustment of the sub-map locations. The terrain registration is accomplished using a two dimensional correlation and a six degree of freedom point cloud alignment method tailored for bathymetric data. The complete bathymetric map is then created from the union of all sub-maps that have been aligned in a consistent manner. Experimental results from the fully automated processing of a multibeam survey over the TAG hydrothermal structure at the Mid-Atlantic ridge are presented to validate the proposed method.This work was funded by the CenSSIS ERC of the Nation Science Foundation under grant EEC-9986821 and in part by the Woods Hole Oceanographic Institution through a grant from the Penzance Foundation

Accurate and discernible photocollages

There currently exist several techniques for selecting and combining images from a digital image library into a single image so that the result meets certain prespecified visual criteria. Image mosaic methods, first explored by Connors and Trivedi[18], arrange library images according to some tiling arrangement, often a regular grid, so that the combination of images, when viewed as a whole, resembles some input target image. Other techniques, such as Autocollage of Rother et al.[78], seek only to combine images in an interesting and visually pleasing manner, according to certain composition principles, without attempting to approximate any target image. Each of these techniques provide a myriad of creative options for artists who wish to combine several levels of meaning into a single image or who wish to exploit the meaning and symbolism contained in each of a large set of images through an efficient and easy process. We first examine the most notable and successful of these methods, and summarize the advantages and limitations of each. We then formulate a set of goals for an image collage system that combines the advantages of these methods while addressing and mitigating the drawbacks. Particularly, we propose a system for creating photocollages that approximate a target image as an aggregation of smaller images, chosen from a large library, so that interesting visual correspondences between images are exploited. In this way, we allow users to create collages in which multiple layers of meaning are encoded, with meaningful visual links between each layer. In service of this goal, we ensure that the images used are as large as possible and are combined in such a way that boundaries between images are not immediately apparent, as in Autocollage. This has required us to apply a multiscale approach to searching and comparing images from a large database, which achieves both speed and accuracy. We also propose a new framework for color post-processing, and propose novel techniques for decomposing images according to object and texture information

Revealing the Invisible: On the Extraction of Latent Information from Generalized Image Data

The desire to reveal the invisible in order to explain the world around us has been a source of impetus for technological and scientific progress throughout human history. Many of the phenomena that directly affect us cannot be sufficiently explained based on the observations using our primary senses alone. Often this is because their originating cause is either too small, too far away, or in other ways obstructed. To put it in other words: it is invisible to us. Without careful observation and experimentation, our models of the world remain inaccurate and research has to be conducted in order to improve our understanding of even the most basic effects. In this thesis, we1 are going to present our solutions to three challenging problems in visual computing, where a surprising amount of information is hidden in generalized image data and cannot easily be extracted by human observation or existing methods. We are able to extract the latent information using non-linear and discrete optimization methods based on physically motivated models and computer graphics methodology, such as ray tracing, real-time transient rendering, and image-based rendering

LIPIcs, Volume 277, GIScience 2023, Complete Volume

LIPIcs, Volume 277, GIScience 2023, Complete Volum

Earth resources: A continuing bibliography with indexes, issue 50

This bibliography lists 523 reports, articles and other documents introduced into the NASA scientific and technical information system between April 1 and June 30, 1986. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economic analysis

Earth resources: A continuing bibliography with indexes

This bibliography lists 579 reports, articles, and other documents introduced into the NASA scientific and technical information system. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economical analysis

Management: A continuing literature survey with indexes, March 1975

A special bibliography listing 1,064 reports, articles, and other documents introduced into the NASA Scientific and Technical Information System in 1974 is presented

Reports of Planetary Geology and Geophysics Program, 1990

Abstracts of reports from NASA's Planetary Geology and Geophysics Program are presented. Research is documented in summary form of the work conducted. Each report reflects significant accomplishments within the area of the author's funded grant or contract