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Lena image quantized to 16, 8, 4 and 2 bits/pixel and distortion measure d(x, y) = | log(x) − log(y)|.
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We study the perceptual problem related to image quantization from an optimization point of view, using different metrics on the color space. A consequence of the results presented is that quantization using histogram equalization provides optimal perceptual results. This fact is well known and widely used but, to our knowledge, a proof has never a...
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Citations
... Object detection and tracking task are performed by utilizing color-based segmentation. To improve the quality of the detection process color quantization (Mota, 2001) is used. To detect object positions, simple color labels are used. ...
... The color image quantization however, is ancillary but still remains very important in image clustering. It is a process to reduce the color distortion quantitatively in the image [6,7,9]. There have been conventional image clustering algorithms in literature and out of these numerous methods, K-means clustering happens to be the simplest and widely used method. ...
... In the paper [6][7][8][16][17][18], the need for color quantization has been discussed to achieve lesser time consumption and the resultant images can be further used for better optimization in results. As in [7][8][9], there is a need to remove redundant pixels that can improve the quantization process in color space. ...
... In the paper [6][7][8][16][17][18], the need for color quantization has been discussed to achieve lesser time consumption and the resultant images can be further used for better optimization in results. As in [7][8][9], there is a need to remove redundant pixels that can improve the quantization process in color space. The PDE method has been used with K-means for quantization [17]. ...
The images acquired in real time outdoor environment are often subject to uneven illumination conditions, cloudy weather, lighting conditions. The instances of partial occlusions deteriorate the background modeling of such scenes. Varying illumination outdoor scene set of images with partial occlusions are addressed through this investigative work. There is a need for a restoration method that finds improved subjective perception and execution time. The proposed work focuses on novel amended exemplar model to improve the subjective perception. The exemplar inpainting method is improved through the color quantization with K-means clustering approach in YCbCr color space. Experimental validations and proposed method results show better improvement in qualitative and objective measures than existing methods. The average “Peak Signal to Noise Ratio (PSNR)” as 28.2869 and “Structural SIMilarity index (SSIM)” as 0.9759 of the proposed method has shown better results respectively both visually and with a tradeoff in time.
... p k refers to the channel's kth level and M to the total channel level. The detection (color thresholding) process is shown in Fig. 2. Color quantization is a type of clustering method that groups similar colors into a threshold value (Mota et al. 2001). Quantization was used to reduce the negative effects of light changes. ...
There have been a great number of studies in the scope of mobile robot systems. The most critical tasks in these systems are control and path planning. The main goal of the control task is to develop a stable control system. On the other hand, the basic motivation in the path planning task is to find a safe path with an acceptable cost. In most researches, a moving robot is considered as a point mass object and only the simulation experiments are applied. In this study, a decision tree-based mobile robot control has been developed for a static indoor environment hosting obstacle(s). The camera has been hung vertically (eye-out-device configuration) to obtain the configuration area map and track the wheeled mobile robot (WMR). A suitable path plan has been extracted with the adaptive artificial potential field (APF) method on the image obtained from the camera. Virtual distance sensors are used to calculate the potentials for APF. A decision tree-based controller has been developed to model the motion characteristics of the robot. A trigonometry-based approach is used to calculate the controller inputs. The controller has steered the WMR on the path in real time. Both simulation and real-world experiments have been conducted on a WMR in different configuration spaces. It has been determined that the designed system is convenient for controlling the WMR. The data obtained are compared to show the difference between the desired and actual path planning results. The efficiency of the controller method has been greatly improved by using dynamic parameters in the control modules.
... The detection process is illustrated in Fig. 4 and scheme is given in Fig. 5. Illumination in the working environment is a problematic issue that causes false segmentation. To overcome this problem, we utilize additional color quantization method [37]. It assumes that masks for thresholding give better results. ...
In this study, a visual servoing go-to-goal behavior controller is designed to control a differential drive mobile robot for a static target. Inputs for the controller method are based on a weighted graph or a triangle trigonometry kinematic model. The controller is designed with general Gaussian function by adapting the differential drive mobile robot dynamics. State parameters of dynamics are obtained by processing images in real time. It is aimed to develop an efficient internal sensor-independent visual-based control method. The single-head camera takes image frames from indoor environment. A real-time tracking process tracks the robot and target in sequential frames. The distances between graph nodes or the angles between edges are assigned as main control inputs according to utilized kinematic model. The velocity of wheels is computed for both models by using the general Gaussian function. We compare our method with two classical control methods that are PID and fuzzy-PID. Control of mobile robot has been made with high accuracy by using the designed visual-based controller.
... Las imágenes de Lena que se presentan han sido cuantificadas utilizando el algoritmo Median Cut empleando 16, 8, 4 y 2 bits / píxel [Mota et al., 2001]. (Ver Gráfica 6). ...
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... 6) Other quantizers: Other quantizers proposed in the literature seek to minimize objective functions specific to their individual problem spaces, utilising additional application specific knowledge. Examples include: perceptual distance quantizers which leverage labelled binary data to symbolize in order to maximise a binary discrimination task [18] and quantizers focusing on maximising quantities such as temporal stability [19] or human perception [20]. Being application specific, unlike the other quantizers detailed, these are not directly applicable to the generalized outlier detection problem considered here. ...
The detection of outliers in time series data is a core component of many data-mining applications and broadly applied in industrial applications. In large data sets algorithms that are efficient in both time and space are required. One area where speed and storage costs can be reduced is via symbolization as a pre-processing step, additionally opening up the use of an array of discrete algorithms. With this common pre-processing step in mind, this work highlights that (1) existing symbolization approaches are designed to address problems other than outlier detection and are hence sub-optimal and (2) use of off-the-shelf symbolization techniques can therefore lead to significant unnecessary data corruption and potential performance loss when outlier detection is a key aspect of the data mining task at hand. Addressing this a novel symbolization method is motivated specifically targeting the end use application of outlier detection. The method is empirically shown to outperform existing approaches.
... Assuming additional, application specific knowledge, these approaches are not applicable to the general class of time-series comparison problems we consider. Other proposed quantizers have included perceptual distance quantizers, which seek to quantize such that as much perceptual information is retained [17], and the Persist algorithm [18] which aims to quantize such that the symbols are persistent temporally with a focus on the human interpretability of the states. While approaching their specific problems from a similar angle to ourselves, the end use, the problems addressed, and the subsequent developments of a custom quantizer, are very different to that presented here. ...
The abundance and value of mining large time series data sets has long been acknowledged. Ubiquitous in fields ranging from astronomy, biology and web science the size and number of these datasets continues to increase, a situation exacerbated by the exponential growth of our digital footprints. The prevalence and potential utility of this data has led to a vast number of time-series data mining techniques, many of which require symbolization of the raw time series as a pre-processing step for which a number of well used, pre-existing approaches from the literature are typically employed. In this work we note that these standard approaches are sub-optimal in (at least) the broad application area of time series comparison leading to unnecessary data corruption and potential performance loss before any real data mining takes place. Addressing this we present a novel quantizer based upon optimization of comparison fidelity and a computationally tractable algorithm for its implementation on big datasets. We demonstrate empirically that our new approach provides a statistically significant reduction in the amount of error introduced by the symbolization process compared to current state-of-the-art. The approach therefore provides a more accurate input for the vast number of data mining techniques in the literature, providing the potential of increased real world performance across a wide range of existing data mining algorithms and applications.
In visual based control (VBC), a single eye-out-device camera provides a limited viewing area. The multi-camera configuration can be used to overcome this problem. However, simultaneous multi-image processing is a challenging task. In this study; a mobile robot control is performed with Gaussian and adaptive potential field based methods under the eye-out device multi-camera configuration. Images taken from the cameras are stitched according to common features. The color based object detection is operated to detect the robot, target and obstacles in this image. To acquire a suitable path between robot and target, adaptive potential field algorithm is executed. The Gaussian based mobile robot controller is used to drive on the robot according to the path plan. In this way, configuration space can be expanded via cameras. At the same time, systematic and unsystematic errors are avoided through VBC. Simulation and real-world experiments show that the system demonstrates a good performance and efficiency.
In this paper, we propose an adaptive perceptual quantization method to convert the representation of High Dynamic Range (HDR) content from the floating point data type to integer, which is compatible with the current image/video coding and display systems. The proposed method considers the luminance distribution of the HDR content, as well as the detectable contrast threshold of the Human Visual System (HVS), in order to preserve more contrast information than the Perceptual Quantizer (PQ) in integer representation. Aiming to demonstrate the effectiveness of this quantizer for HDR video compression, we implemented it in a mapping function on the top of the HDR video coding system based on High Efficiency Video Coding (HEVC) standard. Moreover, a comparison function is also introduced to decrease the additional bit-rate of side information, generated by the mapping function. Objective quality measurements and subjective tests have been conducted in order to evaluate the quality of the reconstructed HDR videos. Subjective test results have shown that the proposed method can improve, in a significant manner, the perceived quality of some reconstructed HDR videos. In the objective assessment, the proposed method achieves improvements over PQ in term of the average bit-rate gain for metrics used in the measurement.
