Digital Image Processing

S. Swetha ¹, K. Ashok Babu ²

Affiliations
1 Sri Indu College of Engineering and Technology, IN
2 Department of Electronics, Sri Indu College of Engineering, JNTU University, Hyd, IN

Abstract

Image retrieval is a challenging task that requires efforts from image processing, link structure analysis, and web text retrieval. Since content-based image retrieval is still considered very difficult, most current large scale web image search engines exploit text and link structure to understand the content of the web images. However, local textual information, such as caption, filenames and adjacent text, is not always reliable and informative. And also, there is no commercial web image search engine support RF because of scalability, efficiency and effectiveness. Therefore, global texture information should be taken into account to support RF and a web image retrieval system makes relevance judgement. In this paper, we propose a re-ranking method to improve web image retrieval by reordering the images retrieved from an image search engine using RF. The re-ranking process should be applicable to any image search engines with little effort and experimental results on a database contain three million web images to show RF is effective.

Keywords

Image Retrieval, Relevance Feedback, Implicit Feedback, RF Fusion.

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T. Sudheer Kumar ¹, K. Ashok Babu ²

Affiliations
1 Sri Indu College of Engineering. & Technology (Affiliated to JNTU, Hyderabad) Ibrahimpatnam, Hyderabad, IN
2 Department (ECE), Sri Indu College of Engg & Technology, IN

Abstract

Analysis and interpretation of an image which was acquired by a non ideal imaging system is the key problem in many application areas. Existing methods to obtain blur invariants which are invariant with respect to centrally symmetric blur are based on geometric moments or complex moments.. In this paper, we propose an alternative approach. We derive the features for image representation which are invariant with respect to blur regardless of the degradation point spread function (PSF) provided that it is centrally symmetric. Methods to obtain blur invariants which are invariants with respect to centrally symmetric blur are based on geometric moments or complex moments, orthogonal Legendre moments. The performance of the proposed descriptors is evaluated with various point-spread functions and different image noises. The comparison of the different approaches with previous methods in terms of pattern recognition accuracy is also provided. The experimental results show that the proposed descriptors are more robust to noise and have better discriminative power than the methods based on geometric or complex moments.

Keywords

Blurred Image, Centrally Symmetric, Legendre Moments, Pattern Recognition, and Symmetric Blur.

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G. Bhavani ¹, K. Ashok Babu ²

Affiliations
1 Dept of ECE (Sub branch)-Digital Systems and Computer Electronics, Sheriguda Village, Ibrahimpatnam, RR-Dist, Andra Pradesh, IN
2 Sri Indu Collage of Engineering, IN

Abstract

An *arial image is the taking of photographs of the ground from an elevated position. The term usually refers to images in which the camera is not supported by a ground-based structure. Cameras may be hand held or mounted, and photographs may be taken by a photographer, triggered remotely or triggered automatically. Platforms for aerial photography include fixed-wing aircraft, helicopters, balloons, blimps and dirigibles, rockets, kites, poles, parachutes, vehicle mounted poles. Aerial photography should not be confused with Air-to-Air Photography, when aircraft serve both as a photo platform and subject.Recently we proposed a wavelet-based dynamic range compression algorithm to improve the visual quality of digital images captured in the high dynamic range scenes with non uniform lighting conditions. Image enhancement algorithm which provides dynamic range compression preserving the local contrast and tonal rendition is a very good candidate in aerial imagery applications such as image interpretation for defense and security tasks. This algorithm can further be applied to video streaming for aviation safety. In this project the latest version of the proposed algorithm which is able to enhance aerial images so that the enhanced images are better then direct human observation, is presented. The results obtained by applying the algorithm to numerous aerial images show strong robustness and high image quality.

Keywords

Aerial Imagery, Wavelet based Arthonormal Decomposition, Quality Enhancement.

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Sachin Pohar ¹, K. Ashok Babu ¹, G. Kesavan Pillai ²

Affiliations
1 Sri Indu College of Engg., Hyd, AP, IN
2 Pricol Limited, Hyd, AP, IN

Abstract

This paper proposes a high capacity reversible image watermarking scheme based on integer to integer wavelet transforms. The proposed scheme divides an input image into non-overlapping blocks and embeds a watermark into the high-frequency wavelet coefficients of each block. The conditions to avoid both underflow and overflow in the spatial domain are embedded includes not only messages but also side information used to reconstruct the exact original image. To minimize the mean squared distortion between the original and the watermarked images given a payload, the watermark is adaptively embedded into the image. The experimental results show that the proposed scheme achieves higher embedding capacity while maintaining distortion at a lower level than the existing reversible watermarking schemes.

Keywords

Reversible Watermarking, Wavelet Transform, Watermark Embedding and Extraction.

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K. Ashok Babu ¹, G. Kesavan Pillai ², Nalla Nandakishore ¹

Affiliations
1 Sri Indu College of Engg., Hyd, AP, IN
2 National Remote Sensing Agency, Hyd, AP, IN

Abstract

Single sensor digital color still/video cameras capture images using a color filter array (CFA) and require color interpolation (demosaicking) to reconstruct full color images. The color reproduction has to combat sensor noises which are channel dependent. If untreated in demosaicking, sensor noises can cause color artifacts that are hard to remove later by a separate Denoising process, because the demosaicking process complicates the noise characteristics by blending noises of different color channels. This paper presents a joint demosaicking-denoising approach to overcome this difficulty. The color image is restored from noisy mosaic data in two steps. First, the difference signals of color channels are estimated by linear minimum mean square-error estimation. This process exploits both spectral and spatial correlations to simultaneously suppress sensor noise and interpolation error. With the estimated difference signals, the full resolution green channel is recovered. The second step involves in a wavelet-based Denoising process to remove the CFA channel-dependent noises from the reconstructed green channel. The red and blue channels are subsequently recovered. Simulated and real CFA mosaic data are used to evaluate the performance of the proposed joint demosaicking-denoising scheme and compare it with many recently developed sophisticated demosaicking and denoising schemes.

Keywords

Bayer Pattern, Color Demosaicking, Color Filter Array (CFA), Denoising, Wavelet.

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K. Ashok Babu , B. A. David , Swapna Medishetty

Abstract

This paper introduces a new implementation of wavelet packet decomposition which is combined with SPIHT (Set Partitioning in Hierarchical Trees) compression scheme. We provide the analysis of the problems arising from the application of zero tree quantization based algorithms (such as SPIHT) to wavelet packet transform coefficients. We established the generalized parent-child relationships for wavelet packets, providing complete tree structures for SPIHT. The proposed algorithm can be used for both wavelet dyadic and Wavelet Packet decomposition (WP-SPIHT). An extensive evaluation of the algorithm was performed and it has been shown that WP-SPIHT significantly outperforms base-line SPIHT coder for texture images. For these images the suboptimal WP cost-function enables good enough energy compaction that is efficiently exploited by the WP-SPIHT.

Keywords

Wavelet, Wavelet Packet, SPIHT, Image Codec.

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