Topic
Run-length encoding
About: Run-length encoding is a research topic. Over the lifetime, 504 publications have been published within this topic receiving 4441 citations. The topic is also known as: RLE.
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Journal Article•
TL;DR: Experimental results show that the modified adaptive run length encoding algorithm can efficiently reduce the length of code when the series code streams have the same length.
Abstract: A modified adaptive run length encoding algorithm was proposed based on a wavelet transform with mathematical morphology.By utilizing morphological dilation,a mass of long series "0" code stream appearing in the bit-plane,adaptive run length encoding algorithm can encode images efficiently.The codeword of the optimal RLC should be equal to the actual length of run length that is corresponding to the total bits of binary code.A salient new feature of the modified adaptive run length encoding algorithm is that the original bit-steam is transformed into the original code length binary encode.Experimental results show that the modified algorithm can efficiently reduce the length of code when the series code streams have the same length.
1 citations
29 Nov 2016
TL;DR: This research proposes a new lossless compression algorithm called YRL that improve RLE using the idea of Relative Encoding, which can treat the value of neighboring pixels as the same value by saving those little differences / relative value separately.
Abstract: Data Compression can save some storage space and accelerate data transfer. Among many compression algorithm, Run Length Encoding (RLE) is a simple and fast algorithm. RLE can be used to compress many types of data. However, RLE is not very effective for image lossless compression because there are many little differences between neighboring pixels. This research proposes a new lossless compression algorithm called YRL that improve RLE using the idea of Relative Encoding. YRL can treat the value of neighboring pixels as the same value by saving those little differences / relative value separately. The test done by using various standard image test shows that YRL have an average compression ratio of 75.805% for 24-bit bitmap and 82.237% for 8-bit bitmap while RLE have an average compression ratio of 100.847% for 24-bit bitmap and 97.713% for 8-bit bitmap.
1 citations
01 Oct 2015
TL;DR: This paper presents a fast implementation of multi-band blending for combining a set of registered images into a composite mosaic with no visible seams and minimal texture distortion, and presents detailed quantitative results compared with OpenCV and Enblend to demonstrate the speed improvements.
Abstract: This paper presents a fast implementation of multi-band blending for combining a set of registered images into a composite mosaic with no visible seams and minimal texture distortion. We first compute a unique seam image using two-pass nearest distance transform, which is independent on the order of input images and has good scalability. Each individual mask can be extracted from this seam image quickly. To promote execution speed and reduce memory usage in building large area mosaics, the seam image and masks are compressed using run-length encoding, and all the following mask operations are built on run-length encoding scheme. The use of run-length encoding for masks processing leads to reduced memory requirements and a compact storage of the mask data. We apply our fast blending system to large scale data sets and present detailed quantitative results compared with OpenCV and Enblend to demonstrate the speed improvements.
1 citations
02 May 2018
TL;DR: The issue of optimizing memory bandwidth to external RAM in FPGA hardware implementation of foreground object segmentation methods is discussed and the proposed solution for ultra high-definition video stream processing was evaluated.
Abstract: In this paper the issue of optimizing memory bandwidth to external RAM in FPGA hardware implementation of foreground object segmentation methods is discussed. Three representative background modelling algorithms: Running Average (RA), Gaussian Mixture Model (GMM) and Pixel Based Adaptive Segmenter (PBAS) and three lossless compression methods: Run Length Encoding (RLE), Huffman coding and Hierarchical Average and Copy Prediction (HACP) with Significant Bit Truncation (SBT) coding were considered. After initial simulations in a software model, it was decided to implement the HACP+SBT approach in hardware. In addition, the possibility of using the proposed solution for ultra high-definition video stream processing was evaluated.
1 citations
Patent•
13 Apr 2011
TL;DR: In this article, a color table with an RLE (Run Length Encoding) compression algorithm is proposed for LOGO pictures. But it is not suitable for large areas of the same color.
Abstract: The invention discloses a picture file compression method which is particularly suitable for LOGO pictures. Based on the characteristics of relatively pure color and large area same color of LOGO pictures, the method adopts a compression mode which combines a color table with an RLE (Run Length Encoding) compression algorithm, i.e. only subscripts in the color table are stored for each pixel dot of a picture, and adjacent dots are represented by using color values and the color number of continuous the same colors. The invention achieves the purpose of keeping high picture compression rate as well as easily operating.
1 citations