Block Edge Detection Research Articles

Perceptual Zero-Tree Coding with Efficient Optimization for Embedded Platforms

This study proposes a block-edge-based perceptual zero-tree coding (PZTC) method, which is implemented with efficientoptimization on the embedded platform. PZTC combines two novel compression concepts for coding efficiency and quality:block-edge detection (BED) and the low-complexity and low-memory entropy coder (LLEC). The proposed PZTC wasimplemented as a fixed-point version and optimized on the DSP-based platform based on both the presented platformindependentand platform-dependent optimization technologies. For platform-dependent optimization, this study examinesthe fixed-point PZTC and analyzes the complexity to optimize PZTC toward achieving an optimal coding efficiency.Furthermore, hardware-based platform-dependent optimizations are presented to reduce the memory size. Theperformance, such as compression quality and efficiency, is validated by experimental results.

Mosaic Defect Detection Based on Macro Block Solid Edge Detection

Mosaic defect detection is a common phenomenon of video defect in Digital video and will degrade the video quality. Therefore, it is more and more important to locate the mosaic and restore the video. Since the macro block is the smallest synchronization unit in the video image and mosaic is occurred in the form of macro block. A mosaic block detection method based on macro block edge detection is proposed in this study. First, the frame image is processed by canny edge detection algorithm to obtain the edge image. Second, the binary edge image is traversed by macro block and determines the solid edge of macro block; finally the mosaic block is determined according to the number of solid edges on every macro block. The experimental results show that the algorithm has good performance.

The Single-Pass Perceptual Embedded Zero-Tree Coding Implementation and Optimization on DSP

In this paper, a block-edge based Single-Pass Perceptual Embedded Zero-tree Coding (SPPEZC) method is proposed and implemented on the DSP-based platform. SPPEZC combines two novel compression concepts which are Block-Edge Detection (BED) and Low-Complexity and Low-Memory Entropy Coder (LLEC) for the coding efficiency and quality. Besides, the proposed SPPEZC is implemented as fixed-point version and optimized on the DSP-based platform based on both the presented platform-independent and platform-dependent optimization technologies. The performance including compression quality and efficiency is validated by experimental results.

The single-pass perceptual embedded zero-tree coding implementation on DSP

This paper proposes a block-edge-based Single-Pass Perceptual Embedded Zero-tree Coding (SPPEZC) method. SPPEZC combines two novel compression concepts, called Block-Edge Detection (BED) and the Low-Complexity and Low-Memory Entropy Coder (LLEC), for coding efficiency and quality. Because the edge information can provide beneficial cues for preserving the perceptual quality of compressed images, this paper presents an effective combinative coding scheme, called Single-Pass Perceptual Embedded Zero-tree Coding (SPPEZC), which integrates the improved LLEC and the block-edge information. This approach provides improved perceptual quality in compressed images. Based on the block-edge information, this paper proposes an adaptive architecture for adjusting the quantization table and subsequently coding the quantized coefficients with the LLEC. The proposed SPPEZC approach was implemented and evaluated on both PC-based and DSP-based embedded platforms. Experimental results and comparisons demonstrate that the proposed SPPEZC technique provides computational efficiency as well as satisfactory perceptual quality in compressed images.

End User Perceptual Distorted Scenes Enhancement Algorithm Using Partition-Based Local Color Values for QoE-Guaranteed IPTV

In this letter, we propose distorted scenes enhancement algorithm in order to provide end user perceptual QoE-guaranteed IPTV service. The block edge detection with weight factor and partition-based local color values method can be applied for the degraded video frames which are affected by network transmission errors such as out of order, jitter, and packet loss to improve QoE efficiently. Based on the result of quality metric after using the distorted scenes enhancement algorithm, the distorted scenes have been restored better than others.