Block Truncation Coding Research Articles

Multi-Level Coding Efficiency with Improved Quality for Image Compression based on AMBTC

In this paper, we have proposed an extended version of Absolute Moment Block Truncation Coding (AMBTC) to compress images. Generally the elements of a bitplane used in the variants of Block Truncation Coding (BTC) are of size 1 bit. But it has been extended to two bits in the proposed method. Number of statistical moments preserved to reconstruct the compressed has also been raised from 2 to 4. Hence, the quality of the reconstructed images has been improved significantly from 33.62 to 38.12 with the increase in bpp by 1. The increased bpp (3) is further reduced to 1.75in multiple levels: in one level, by dropping 4 elements of the bitplane in such a away that the pixel values of the dropped elements can easily be interpolated with out much of loss in the quality, in level two, eight elements are dropped and reconstructed later and in level three, the size of the statistical moments is reduced. The experiments were carried over standard images of varying intensities. In all the cases, the proposed method outperforms the existing AMBTC technique in terms of both PSNR and bpp.

High Capacity Reversible Data Hiding in AMBTC-Compressed Images

This paper proposes a high capacity reversible data hiding scheme in images compressed by absolute moment block truncation coding (AMBTC). The quantization levels of compressed blocks are employed as cover media, and some extra confidential data are hidden in it based on a multilevel histogram shifting mechanism. The transmission system preserves the same complexity. Moreover, the reconstructed image quality is exactly the same as the original compressed version due to the reversibility. Extensive experimental results demonstrate the effectiveness of the proposed scheme.

A COLOR IMAGE AUTHENTICATION AND RECOVERY METHOD USING BLOCK TRUNCATION CODE EMBEDDING

A new method for color image authentication and recovery is proposed in this paper. To achieve this goal, the least significant bit (LSB) and the second LSB of the spatial domain were selected to embed the watermark. The watermark consists of two parts: authentication data and recovery data made by block truncation code and bitmap. According to the experimental results, the image embedded within the authentication data and recovery data can still preserve high image quality. The results also reveal that the tampered images can be successfully recovered with acceptable visual quality.

Dual block truncation coding for overdriving of full HD LCD driver

This paper presents an image coding method for overdriving of a 10bit Full HD LCD display considering the chip size of TCON (Timing Controller) and real-time operation. The proposed method is an adaptive scheme of AM-BTC (Absolute Moment Block Truncation Coding). It splits a sample block into two sub-blocks considering the color level distribution of the sample block and applies AMBTC to each sub-block. Experimental results show that the proposed method is superior to the conventional method in both objective and subjective visual quality.

Improved Face Recognition with Multilevel BTC using Kekre’s LUV Color Space

The theme of the work presented in the paper is Multilevel Block Truncation Coding based Face Recognition using the Kekre’s LUV (K’LUV) color space. In [1], Multilevel Block Truncation Coding was applied on the RGB color space up to four levels for face recognition. The experimental results showed that Block Truncation Coding Level 4 (BTC-level 4) was better as compared to other BTC levels of RGB color space. Results displaying a similar pattern are realized when the K’LUV color is used. It is further observed that K’LUV color space gives improved results on all four levels.

Multi-Level Coding Efficiency with Improved Quality for Image Compression based on AMBTC

In this paper, we have proposed an extended version of Absolute Moment Block Truncation Coding (AMBTC) to compress images. Generally the elements of a bitplane used in the variants of Block Truncation Coding (BTC) are of size 1 bit. But it has been extended to two bits in the proposed method. Number of statistical moments preserved to reconstruct the compressed has also been raised from 2 to 4. Hence, the quality of the reconstructed images has been improved significantly from 33.62 to 38.12 with the increase in bpp by 1. The increased bpp (3) is further reduced to 1.75in multiple levels: in one level, by dropping 4 elements of the bitplane in such a away that the pixel values of the dropped elements can easily be interpolated with out much of loss in the quality, in level two, eight elements are dropped and reconstructed later and in level three, the size of the statistical moments is reduced. The experiments were carried over standard images of varying intensities. In all the cases, the proposed method outperforms the existing AMBTC technique in terms of both PSNR and bpp.

Color &Texture Based Image Retrieval using Fusion of Modified Block Truncation Coding (MBTC) and Kekre Transform Patterns

Content Based Image Retrieval is an interesting topic of research. This paper is about image content-based image search. Specifically, it is on developing technologies for bridging the semantic gap that currently prevents wide-deployment of image content-based search engines. Mostly, content-based methods are based on low-level descriptions, while high-level or semantic descriptions are beyond current capabilities. In this paper a CBIR is proposed based on color & texture based search. Modified Block Truncation Coding (MBTC) is used for color information retrieval. To extract texture information we are using pattern generated by transforms, currently we are considering Kekre Transform. The feature vector is generated by fusion of above mentioned techniques.

Implementation of Multimode-Multilevel Block Truncation Coding for LCD Overdrive

Implementation of Multimode-Multilevel Block Truncation Coding for LCD Overdrive

Very Low Cost Design and Implementation of Block Truncation Coding for Image Compression

Very Low Cost Design and Implementation of Block Truncation Coding for Image Compression

A fast progressive image transmission scheme using block truncation coding by pattern fitting

In this paper, we have proposed a novel progressive image transmission scheme. In the present method, the concept of the BTC-PF is used for faster decoding. Here, images are decomposed into a number of blocks based on smoothness criterion. The smooth blocks are encoded by block means and the others are by BTC-PF method. To encode a block by BTC-PF method, the codebook is organized like a full search progressive transmission tree which helps greatly in efficient progressive transmission. The present method provides good image quality at low bit-rate and faster decoding compared to other spatial domain progressive transmission methods. We extend this method for color images also. In color image coding, each color plane is encoded separately and then the encoded information of the planes are transmitted in interleaving manner to obtain color images right from the early stages.

Improved Block Truncation Coding Using Extreme Mean Value Scaling and Block-Based High Speed Direct Binary Search

Block truncation coding (BTC) has been considered as an efficient compression technique for decades. However, the annoying blocking effect and false contour caused by low bit rate configuration are key problems. To solve these problems, many former halftoning-based BTCs are proposed. However, these schemes also induce another impulse noise issue while the previous issues still have room for improvement. To cope with this, the iteration-based halftoning is combined with BTC, namely Direct-Binary-Search BTC (DBSBTC) to solve the aforementioned problems. Moreover, the high-speed DBS halftoning method along with the block-based strategy yield even faster processing speed than some of the former halftoning-based BTC schemes. As documented in the experimental results, the proposed DBSBTC is superior to the former halftoning-base BTC schemes in terms of image quality, and which makes the former schemes as potential candidates for surveillance and computer vision applications.

A Blind Image Watermarking Scheme Utilizing BTC Bitplanes

This paper presents a novel image watermarking scheme utilizing Block Truncation Coding (BTC). This scheme uses BTC to guide the watermark embedding and extraction processes. During the embedding process, the original cover image is first partitioned into non-overlapping 4×4 blocks. Then, BTC is performed on each block to obtain its BTC bitplane, and the number of ‘1’s in the bitplane is counted. If the watermark bit to be embedded is ‘1’ and the number of ‘1’s is odd, or the watermark bit to be embedded is ‘0’ and the number of ‘1’s is even, then no change is made. Otherwise, by changing at most three pixels in the original image block, the number of ‘1’s (or ‘0’s) in the renewed bitplane are forced to be odd for the watermark bit ‘1’ or to be even for the watermark bit ‘0’. During the extraction process, BTC is first performed on each block to obtain its bitplane. If the number of ‘1’s in the bitplane is odd, then the embedded watermark bit is ‘1’. Otherwise, the embedded watermark bit is ‘0’. The experimental results show that the proposed watermarking method is semi-fragile except for the changes in brightness and contrast; therefore, the proposed method can be used for image authentication.

Block Truncation Coding using Enhanced Interpolations and Lookup Procedures for Image Compression

ABSTRACT Block Truncation Coding is one of the easy and efficient techniques for lossy image compression. In this paper, we have proposed few methods to enhance the existing Interpolative and Lookup procedures to reduce the bitrate and to improve the PSNR obtained with the Block Truncation Coding (BTC) based image compression methods. Of the existing BTC based methods, we have implemented the Minimum Mean Square Error (MMSE) method which gives better PSNR (quality of the reconstructed images) value to generate the bitplane and statistical moments. The size of the bitplane is reduced using Interpolation and Lookup procedures with noticeable degradation in PSNR value. This degradation is minimized using the proposed methods. Hence the proposed methods give less bitrate and better PSNR, when compared to the existing methods. General Terms Image Compression, Block Truncation Coding, Interpolative Techniques and Lookup Procedure. Keywords Image compression, bit-rate, bit-plane, BTC, PSNR, MMSE, Interpolation.

Feature Extraction using Overlap Blocks for Content based Image Retrieval

The paper presents an extension of content based image retrieval (CBIR) techniques based on Overlap Modified Block Truncation Coding (BTC) and Overlap Gabor Magnitude. Modified Block truncation coding based features is one of the CBIR methods proposed using color features of image. The approach basically considers red, green and blue planes of an image to compute feature vector. This MBTC based CBIR can be extended as Overlap Modified BTC for performance improvement in image retrieval. The Overlap Gabor Magnitude technique is used for texture features of image. The CBIR techniques like MBTC, Gabor and Fusion of MBTC and Gabor are further modified using overlap blocs technique to analyze and compare their performances. The proposed CBIR technique is implemented on a database having 1000 images spread across 11 categories and COIL image database having 1080 images spread across 15 categories. For each proposed CBIR technique 55 queries (5 per category) are fired on the database and net average precision and recall are computed. The results have shown performance improvement (higher precision and recall values) with Overlap (Fusion technique , Gabor Magnitude and Modified BTC compared to Non-Overlap (Fusion technique , Gabor Magnitude and Modified BTC ).In all Overlap technique based CBIR system gives best performance.. General Terms Algorithm, Performance

A high quality and small shadow size visual secret sharing scheme based on hybrid strategy for grayscale images

Many secret sharing schemes for digital images have been developed in recent decades. Traditional schemes typically must deal with the problem of computational complexity, and other visual secret sharing schemes come with a higher transmission cost and storage cost; that is, each shadow size is m times as big as the original secret image. The new ( 2 , n ) secret sharing scheme for grayscale images proposed in this paper is based a combination of acceptable image quality using block truncation coding (BTC), high compression ratio discrete wavelet transform (DWT) and good subjective performance of the vector quantization (VQ) technique. Experimental results confirm that our proposed scheme not only generates a high quality reconstructed original image but also generates small, random-like grayscale shadows.

Lapped transform‐based codec for frame‐memory reduction in super‐quality LCD overdrive

Abstract— Overdrive is commonly used to reduce the liquid‐crystal response time and motion blur in liquid‐crystal displays (LCDs). However, overdrive requires a large frame memory in order to store the previous frame for reference. In this paper, a lapped transform‐based codec (LTC) is proposed to reduce the frame memory needed for LCD overdrive. In the latest literature, a directional prediction‐based codec (DPC) employs eight directional predictions, which takes up a large percentage of the computational complexity of the codec and does not consider the de‐correlation of the inter‐blocks. Therefore, the LTC first uses the lapped transform to decompose the correlation of the inter‐blocks in the YUV color space. A hadamard transform is then used for energy compaction. The reordered coefficients are pre‐quantized and encoded using the proposed adaptive bit‐plane coding (ABPC) method for a simple hardware implementation. The simulation results show that the proposed LTC significantly improves the DPC in both subjective and objective performance and outperforms the block truncation coding (BTC) and adaptive multi‐level BTC (AM‐BTC), which have been described in the literature.

High performance reversible data hiding for block truncation coding compressed images

Reversible data hiding has been a hot research topic because it can recover both the host media and hidden data without distortion. Because most digital images are stored and transmitted in compressed forms, such as JPEG, vector quantization, and block truncation coding (BTC), the reversible data hiding schemes in compressed domains have been paid more and more attention. Compared with transform coding, BTC has a significantly low complexity and less memory requirement, it therefore becomes an ideal data hiding domain. Traditional data hiding schemes in the BTC domain modify the BTC encoding stage or BTC-compressed data according to the secret bits, and they have a relatively low efficiency and meanwhile may reduce the image quality. This paper presents a novel reversible data hiding scheme based on the joint neighbor coding technique for BTC-compressed images by further losslessly encoding the BTC-compressed data according to the secret bits. First, BTC is performed on the original image to obtain the BTC-compressed data that can be represented by a high mean table, a low mean table, and a bitplane sequence. Then, the secret data are losslessly embedded in both the high mean and low mean tables. Our hiding scheme is a lossless method based on the relation among the current value and the neighboring ones in mean tables. In addition, it can averagely embed 2 bits in each mean value, which increases the capacity and efficiency. Experimental results show that our scheme outperforms three existing BTC-based data hiding works, in terms of the bit rate, capacity, and efficiency.

An algorithm for binary codebook design based on the average bitmap replacement error (ABPRE)

In this paper, an algorithm for binary codebook design has been used in vector quantization technique, which is used to improve the acceptability of the absolute moment block truncation coding (AMBTC) method. Vector quantization (VQ) method is used to compress the bitmap (the output proposed from the first method (AMBTC)). In this paper, the binary codebook can be engender for many images depending on randomly chosen to the code vectors from a set of binary images vectors, and this codebook is then used to compress all bitmaps of these images. The chosen of the bitmap of image in order to compress it by using this codebook based on the criterion of the average bitmap replacement error (ABPRE). This paper is suitable to reduce bit rates (increase compression ratios) with little reduction of performance (PSNR).

An algorithm for binary codebook design based on the average bitmap replacement error (ABPRE)

In this paper, an algorithm for binary codebook design has been used in vector quantization technique, which is used to improve the acceptability of the absolute moment block truncation coding (AMBTC) method. Vector quantization (VQ) method is used to compress the bitmap (the output proposed from the first method (AMBTC)). In this paper, the binary codebook can be engender for many images depending on randomly chosen to the code vectors from a set of binary images vectors, and this codebook is then used to compress all bitmaps of these images. The chosen of the bitmap of image in order to compress it by using this codebook based on the criterion of the average bitmap replacement error (ABPRE). This paper is suitable to reduce bit rates (increase compression ratios) with little reduction of performance (PSNR).

Lossless Data Embedding in BTC Codes Based on Prediction and Histogram Shifting

This paper proposes a lossless data embedding method for Block Truncation Coding (BTC) compressed images based on prediction and histogram shifting techniques. Because BTC is easy to implement, and requires significantly less CPU cost, it has arouse widely attention in applications where real-time processing is demanded. For the existing lossless data embedding method in BTC codes, the decoder has to be specifically designed so that the spatial domain image can perfectly reconstructed from the compressed codes. Therefore, the application of these methods is limited. In the proposed embedding method, we slightly modified the quantization values of BCT codes to embed data losslessly, and a standard BTC decoder can be used to decode the BTC codes. The embedded secret messages can be extracted at the receiver side with the correct key. The experimental results revealed that the proposed method not only recovers the stego image to its original one, but also preserved a high image quality.