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H.264/AVC is the latest international video coding standard. It was jointly developed by the Video Coding Experts Group (VCEG) of the ITU-T and the Moving Picture Experts Group (MPEG) of ISO/IEC. The goals of this standardization effort were enhanced compression efficiency and network friendly video representation. Because H.264 includes a lot of new characteristics and offers a lot of tools for compression, it can improve the quality of the compressed image greatly. H.264/AVC provides gains in compression efficiency of up to 50\% over a wide range of bit rates and video resolutions compared to previous standards. Object-based coding is the new feature that MPEG-4 supports. The object-based coding can reduce the region of motion estimation; this will increase the speed of coding. The output frame can be combined with the object-based coding sequence and also can be synthesized with the object-based coding sequence. Taking the advantage of the H.264/AVC and Object-based coding, the coding will be faster and the sequence will be smaller. In this thesis, we adopted the H.264/AVC video coding standard to implement the object coding.

This thesis focusses on whether words are treated like visual objects by the human attentional system. Previous research has shown an attentional phenomenon that is associated specifically with objects: this is known as “object based attention” (e.g. Egly, Driver & Rafal, 1994). This is where drawing a participant’s attention (cuing) to any part of a visual object facilitates target detection at non-cued locations within that object. That is, the cue elevates visual attention across the whole object. The primary objective of this thesis was to demonstrate this effect using words instead of objects. The main finding of this thesis is that this effect can indeed be found within English words – but only when they are presented in their canonical horizontal orientation. The effect is also highly sensitive to the type of cue and target used. Cues which draw attention to the “wholeness” of the word appear to amplify the object based effect. A secondary finding of this thesis is that under certain circumstances participants apply some form of attentional mapping to words which respects the direction of reading. Participants are faster (or experience less cost) when prompted to move their attention in accord with reading direction than against. This effect only occurs when the word stimuli are used repeatedly during the course of the experiment. The final finding of this thesis is that both the object based attentional effect and the reading direction effect described above can be found using either real words or a non-lexical stimulus: specifically symbol strings. This strongly implies that these phenomena are not exclusively associated with word stimuli, but are instead associated with lower level visual processing. Nonetheless, it is considered highly likely that these processes are involved in the day to day process of reading.

Comment les différents aspects d'une scène visuelle sont-ils encodés en mémoire visuelle à court-terme (MVCT) ? S'il est communément admis que la MVCT ne peut stocker simultanément qu'un nombre extrêmement limité d'informations, la question du format des représentations est actuellement loin d'être résolue. Cette thèse avait pour objectif d'étudier les influences de l'organisation perceptive des différents éléments d'une scène visuelle sur la capacité de stockage de la MVCT. Pour ce faire, dix expériences, utilisant le paradigme de détection de changement (c'est-à-dire en présentant deux séries de stimuli séparées par un court laps de temps et en demandant aux participants de détecter un éventuel changement entre ces deux séries) ont été réalisées. La principale manipulation expérimentale était la comparaison entre différentes organisations perceptives des stimuli dans le champ visuel. Les résultats de nos recherches ont contribué de façon significative à une meilleure compréhension de la façon dont les différents aspects d'une scène visuelle sont traités et encodés en MVCT et suggèrent l'existence de différents types de représentations organisées hiérarchiquement. Tout d'abord, les relations spatiales entre tous les éléments d'une scène visuelle seraient encodées sous la forme d'une configuration spatiale. Cette représentation configurale permettrait, dans un deuxième temps, l'analyse et l'encodage de l'identité individuelle des différents éléments. A ce niveau, nous avons montré que le nombre d'éléments pouvant être simultanément encodés et maintenus en MVCT pourrait dépendre considérablement de la manière dont ils sont présentés dans le champ visuel des participants. Ainsi, lorsque différents traits (couleur, forme, texture, orientation, etc.) occupent la même localisation spatiale, formant ainsi une même partie d'un objet, ils seraient traités et encodés aussi efficacement qu'un simple trait. Dans ce cas, la capacité de stockage de la MVCT doit être comprise en terme d'objets intégrés. Par contre, lorsque les traits d'un objet sont spatialement séparés les uns des autres, constituant différentes parties d'objets, le nombre d'éléments pouvant être simultanément encodés en MVCT est fonction du nombre de traits présents dans le champ visuel, et non du nombre d'objets. L'organisation perceptive des informations visuelles a donc une influence directe sur le nombre d'éléments pouvant être simultanément encodés en MVCT en modifiant la nature des représentations./ How are the different aspects of a visual scene encoded in visual short-term memory (VSTM)? Although it is acknowledged that only a small number of information can be simultaneously stored in VSTM, the format of representation is far to be understood. The goal of the present thesis was to study the perceptual influences of the items in a visual scene on the VSTM storage capacity. Ten experiments, using the change detection paradigm (i.e., two stimuli arrays were presented and separated by a short period of time, and the task was to detect a possible change between the two arrays) were conducted. The major experimental manipulation was to contrast different perceptual organisations of the stimuli in an array. The results of those experiments have significantly contributed to a better understanding about how the different aspects of a visual scene are processed and encoded in VSTM and suggest the existence of different types of representation, hierarchically organised. Firstly, the spatial relations between items in a visual scene would be encoded though spatial configuration. Then, this configural representation would allow the processing and the encoding of the identities of each individual item. Here, the number of items that can be simultaneously encoded in VSTM might greatly depend on the way they are presented in the visual field. Indeed, we provided evidence that visual features (colour, shape, texture, orientation), that share the same spatial location, are encoded in VSTM as accurately as single features. In that case, the VSTM storage capacity must be understood in terms of integrated objects rather than in terms of single features. In contrast, when visual features are spatially distributed over different spatial locations, the limitation in the storage capacity is function of the number of features. The perceptual organisation of the visual information has thus a direct influence on the number of items that can be simultaneously encoded in VSTM by modulating the nature of representations.

Bottomland hardwood forests are highly productive ecosystems which perform many important ecological services. Unfortunately, many bottomland hardwood forests have been degraded or lost. Accurate land cover mapping is crucial for management decisions affecting these disappearing systems. SPOT-5 imagery from 2005 was combined with Light Detection and Ranging (LiDAR) data from 2006 and several ancillary datasets to map a portion of the bottomland hardwood system found in the Sulphur River Basin of Northeast Texas. Pixel-based classification techniques, rulebased classification techniques, and object-based classification techniques were used to distinguish nine land cover types in the area. The rule-based classification (84.41% overall accuracy) outperformed the other classification methods because it more effectively incorporated the LiDAR and ancillary datasets when needed. This output was compared to previous classifications from 1974, 1984, 1991, and 1997 to determine abundance trends in the area’s bottomland hardwood forests. The classifications from 1974-1991 were conducted using identical class definitions and input imagery (Landsat MSS 60m), and the direct comparison demonstrates an overall declining trend in bottomland hardwood abundance. The trend levels off in 1997 when medium resolution imagery was first utilized (Landsat TM 30m) and the 2005 classification also shows an increase in bottomland hardwood from 1997 to 2005, when SPOT-5 10m imagery was used. However, when the classifications are re-sampled to the same resolution (60m), the percent area of bottomland hardwood consistently decreases from 1974-2005. Additional investigation of object-oriented classification proved useful. A major shortcoming of object-based classification is limited justification regarding the selection of segmentation parameters. Often, segmentation parameters are arbitrarily defined using general guidelines or are determined through a large number of parameter combinations. This research justifies the selection of segmentation parameters through a process that utilizes landscape metrics and statistical techniques to determine ideal segmentation parameters. The classification resulting from these parameters outperforms the classification resulting from arbitrary parameters by approximately three to six percent in terms of overall accuracy, demonstrating that landscape metrics can be successfully linked to segmentation parameters in order to create image objects that more closely resemble real-world objects and result in a more accurate final classification.

Abstract Since the establishment of World Wide Web in 1989, the life cycle of knowledge has been greatly shortened, which forces people to be more efficient in the creation, value-adding, update, exchange and use of knowledge. Thus, how to ¡§digitalize¡¨ and ¡§itemize¡¨ knowledge and the learning contents to form a more efficient knowledge cycle has become a crucial concern for one¡¦s competitiveness. Facing the new era of high-speed info, the traditional teaching approach has failed to meet the requirements of the ever-changing learning environment. Therefore, both the design and method of teaching should be changed in a great way in order to keep up with the ongoing development of the entire environment. We have to re-evaluate both the advantages and disadvantages of the Internet¡¦s influences on teaching, and develop a corresponding design module and assessment method, instead of merely digitalizing the traditional teaching materials, or just leaving it alone. If the learning contents could achieve the goal of being Reusable, Accessible, Durable, Interoperable and Adaptable, 50 ~ 80% of expense on developing new teaching materials will be saved. As a result, the main emphasis of this study lies on developing an Object-based E-learning Instructional Design Model which is adaptable to the itemization of conceptual learning. It will discuss the feasibility and effect of employing different multi-media and Example & Enquiry Strategy in the design of Internet Teaching Material Design. This study utilized Teaching Experiment Design, Pre- and Post- experiment, questionnaire assessment in gathering necessary information, which is concluded as below: 1. Teaching materials designed according to the Object-based E-learning Instructional Design Model is easier to understand, interest-provoking, and is adaptable to changes made along side with current events. 2. No significant difference shows among different media platforms of teaching materials generated under Object-based E-learning Instructional Design Model. 3. The ¡§simulation¡¨ method in ¡§Example & Enquiry Strategy¡¨ performed better effect than ¡§instructional games¡¨on the ¡§satisfaction of example & enquiry¡¨. Those who had experienced interaction and enquiry strategy have better learning grades than those who had not. 4.Personal traits and contents of teaching materials have remarkable interference with the learning effect of Object-based E-learning Materials. Keywords¡GObject-based¡BE-learning¡BInstructional Design¡BConceptual Learning¡BTeaching Achievement

Image classification based on remotely sensed data is the primary domain of automatic mapping research. With the increasing of urban development, keeping geographic database updating is imminently needed. Automatic mapping of land cover types in urban area is one of the most challenging problems in remote sensing. Traditional database updating is time consuming and costly. It has usually been performed by manual observation and visual interpretation, In order to improve the efficiency as well as the accuracy, new technique in the data collection and extraction becomes increasingly necessary. This paper studied an object-based decision tree classification based on orthophoto and lidar data, both alone and integrated. Four land cover types i.e. Forest, Water, Openland as well as Building were successfully extracted. Promising results were obtained with the 89.2% accuracy of orthophoto based classification and 88.6% accuracy of lidar data based classification. Both lidar data and orthophoto showed enough capacity to classify general land cover types alone. Meanwhile, the combination of orthophoto and lidar data demonstrated a prominent classification results with 95.2% accuracy. The results of integrated data revealed a very high agreement. Comparing the process of using orthophoto or lidar data alone, it reduced the complexity of land cover type discrimination. In addition, another classification algorithm, support vector machines (SVM) classification was preformed. Comparing to the decision tree classification, it obtained the same accuracy level as decision tree classification in orthophoto dataset (89.2%) and integration dataset (97.3%). However, the SVM results of lidar dataset was not satisfactory. Its overall accuracy only reached 77.1%. In brief, object-based land cover classification demonstrated its effectiveness in land cover map generation. It could exploit spectral and spatial features from input data efficiently and classifying image with high accuracy.

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This thesis presents a comparison of two methods for Object-Based Unequal Error Protection. The two methods, Combined Unequal Error Protection and Individual Unequal Error Protection, add Forward Error Correcting Codes to embeddedly coded objects of an image. This is done so that each byte within an object is protected according to its importance, has object-level of error protection proportional to the object's importance to the reconstructed quality, and has random access at the receiver. It is found that random access to the objects is obtained at a cost in terms of quality.