Compound image compression for real-time computer screen image transmission

Abstract

Abstract-We present a compound image compression algorithm for real-time applications of computer screen image transmission. It is called shape primitive extraction and coding (SPEC). Real-time image transmission requires that the compression algorithm should not only achieve high compression ratio, but also have low complexity and provide excellent visual quality. SPEC first segments a compound image into text/graphics pixels and pictorial pixels, and then compresses the text/graphics pixels with a new lossless coding algorithm and the pictorial pixels with the standard lossy JPEG, respectively. The segmentation first classifies image blocks into picture and text/graphics blocks by thresholding the number of colors of each block, then extracts shape primitives of text/graphics from picture blocks. Dynamic color palette that tracks recent text/graphics colors is used to separate small shape primitives of text/graphics from pictorial pixels. Shape primitives are also extracted from text/graphics blocks. All shape primitives from both block types are losslessly compressed by using a combined shape-based and palette-based coding algorithm. Then, the losslessly coded bitstream is fed into a LZW coder. Experimental results show that the SPEC has very low complexity and provides visually lossless quality while keeping competitive compression ratios.Index Terms-Compound image compression, compound image segmentation, palette-based coding, shape-based coding, shape primitive extraction.

Personalized and efficient social image transmission scheme in mobile wireless network

“…Image data transmission techniques have been studied for about 20 years [1,8,11,15,23,24]. The stateof-the-art methods can be mainly divided into two categories: 1) improvement design of transmission protocol [1,2,8,10,11,23]; and 2) image data encoding and compression [4-7, 12, 15, 21, 24, 27].…”

“…Since most image transmission methods use the same pixel interpolation scheme for the entire picture, without considering the differences in different portions, Chang et al [4] presented a progressive image transmission(PIT) scheme which transmits the most significant portion of a picture, followed by less important parts. Lin et al [15] presented a compound image compression algorithm for real-time applications of computer screen image transmission called Shape Primitive Extraction and Coding(SPEC). Ruiz et al [24] designed an image compression algorithm to support progressive image transmission.…”

Analysis of coding tools and improvement of text readability for screen content

“…To further enhance these methods, motion compensation is added in [7] and a LempelZiv-Markov algorithm is applied to exploit repetitive patterns in text areas. In [9] the image blocks are classified into categories dependant on their type of content and are treated accordingly. Since in all of those publications additional modes are added for special image contents like text or graphics, a lot of supplementary encoder complexity is introduced.…”

“…The most important difference is that the structure of the resulting bit stream is incompatible to AVC and thus needs special decoders while the proposed approach is fully compatible with the AVC standard. However, both [4] and [9] applied their approach to still images. Virtual Network Computing (VNC), a crossplatform implementation of the Remote Framebuffer Protocol (RFB), contains a number of different encoding algorithms for SC [12] between which the user can choose.…”

Perceptual Quality Measure of Screen Content Images

“…For fast sharing in-between different devices, it is important to acquire, compress, store or transmit SCIs efficiently. Many solutions have been proposed to process SCIs, which including segmentation and compression of SCIs [4]. MPEG/VCEG called for proposals to efficiently compress screen content image/videos as an extension of the HEVC standard, and many other proposals have been reported to address this need.…”