Publications

Permanent URI for this collectionhttps://ir.daiict.ac.in/handle/123456789/32

Browse

Filters

2005 - 200942010 - 201919

Settings

Author: search.filters.author.Joshi, Manjunath VEnd date: 2019

Search Results

Now showing 1 - 10 of 23
  • Thumbnail Image
    PublicationMetadata only
    Multi-resolution Image Fusion in Remote Sensing
    (Cambridge University Press, Cambridge, 2019-03-01) Joshi, Manjunath V; Upla, Kishor p
  • Thumbnail Image
    PublicationMetadata only
    Digital heritage reconstruction using super-resolution and inpainting
    (Morgan & Claypool, California, 2017-01-01) Padalkar, Milind G; Joshi, Manjunath V; Khatri, Nilay L
  • Thumbnail Image
    PublicationMetadata only
    Motion-Free Super-Resolution
    (Springer, New York, 2005-07-06) Chaudhuri, Subhasis; Joshi, Manjunath V
  • Thumbnail Image
    PublicationMetadata only
    Design of Complex Adaptive Multiresolution Directional Filter Bank and Application to Pansharpening
    (Springer, 01-02-2017) Gajbhar, Shrishail S; Joshi, Manjunath V; Joshi, Manjunath V; Joshi, Manjunath V; Joshi, Manjunath V; Joshi, Manjunath V; Joshi, Manjunath V; DA-IICT, Gandhinagar; Gajbhar, Shrishail S (201121016)
    This paper proposes a new 2-D transform design, namely�complex adaptive multiresolution directional filter bank, to represent the spatial orientation features of an input image�adaptively. The proposed design is completely�shift invariant�and represents the input image by one low-pass and multiscale�N�directional band-pass subbands. Here,�N�represents estimated number of dominant directions present in the input image. Our design consists of two main filter bank stages. A fix partitioned complex-valued directional filter bank (CDFB) is at the core of the design followed by a novel partition filter bank stage. Fine partitioning of the CDFB subbands is used to get the adaptive nature of the proposed transform. The partitioning decision is made based on the directional significance of range of CDFB subband angle selectivity in the input image. Partition filter bank stage which�nonuniformly�partitions the CDFB subbands provides total�N�dominant direction selective subbands. Local orientation map of the input image is used to determine the dominant directions and hence�N. For better sparsity properties, we design the multiresolution stage with filters having high�vanishing moments�and better frequency selectivity. Applicability of the proposed adaptive design is shown for pansharpening of multispectral images. Our proposed pansharpening approach is evaluated on images captured using QuickBird and IKONOS-2 satellites. Results obtained using the proposed approach on these datasets show considerable improvements in qualitative as well as quantitative evaluations when compared to state-of-the-art pansharpening approaches including transform-based methods.
  • Thumbnail Image
    PublicationMetadata only
    Abundance estimation using discontinuity preserving and sparsity-induced priors
    (IEEE, 30-05-2019) Patel, Jignesh R; Joshi, Manjunath V; Bhatt, Jignesh S; Joshi, Manjunath V; Joshi, Manjunath V; Joshi, Manjunath V; Joshi, Manjunath V; Joshi, Manjunath V; DA-IICT, Gandhinagar; Patel, Jignesh R (201521011)
    Abundance estimation is used to infer the proportions of endmembers with the given endmember signatures and reflectance value at each location. In this paper, we propose a two-phase iterative approach to estimate the abundances (fractions) of materials (endmembers) from the pixels of hyperspectral images (HSIs) by using the energy minimization framework. A linear mixture model is used to define the data term. We observe that abundance maps have homogeneous regions with limited discontinuity, and they exhibit spatial redundancy. Hence, we use inhomogeneous Gaussian Markov random field (IGMRF) and sparsity-induced priors as the regularization terms. While the IGMRF prior captures the smoothness and preserves discontinuities among abundance values, the sparsity-induced prior accounts for redundancy. We calculate the IGMRF parameters at every pixel location and learn a dictionary and the sparse representation for abundances using the initial estimate in phase 1, while the final abundance maps are estimated in phase 2. In order to learn the sparsity, we use the approach based on K-singular value decomposition. Both the IGMRF and sparseness parameters are initialized using an initial estimate of abundances and refined using the two-phase iterative approach. The experiments are conducted on synthetic hyperspectral HSIs with different noise levels, as well as on two real HSIs. The results are qualitatively and quantitatively compared with state-of-the-art approaches. Experimental results demonstrate the effectiveness of the proposed approach.
  • Thumbnail Image
    PublicationMetadata only
    SNR wall for generalized energy detector in the presence of noise uncertainty and fading
    (Elsevier, 01-02-2019) Captain, Kamal; Joshi, Manjunath V; Joshi, Manjunath V; Joshi, Manjunath V; Joshi, Manjunath V; Joshi, Manjunath V; Joshi, Manjunath V; DA-IICT, Gandhinagar; Captain, Kamal (201321003)
    The performance of energy detection (ED) degrades under low�SNR, noise uncertainty (NU) and fading. The generalized energy detector (GED) is obtained by changing the squaring operation in ED by an arbitrary positive number�. In this paper, we investigate the signal to noise ratio (SNR) wall for GED under diversity considering NU as well as fading by considering�-Law combining (pLC) and�law selection (pLS) diversity. First, the�SNR�walls considering�AWGN�channel are derived. It is shown that for pLC diversity, increasing��results in lower�SNR�wall. It is also shown that under no diversity and pLS diversity, the�SNR�wall is independent of�. The analysis is then extended to the channel with Nakagami fading where it is shown that the SNR wall increases significantly. As a byproduct of this work, we also study the effect of NU and fading on the detection performance and show that above certain value, the effect of NU is more severe when compared to the fading. The effect of��on the performance is analyzed and it is shown that the performance is the best for values of��close to 2. The performance of pLC and pLS is also compared.
  • Thumbnail Image
    PublicationMetadata only
    A regularized pan-sharpening approach based on self-similarity and Gabor prior
    (Taylor & Francis, 01-01-2017) Upla, Kishor P; Joshi, Manjunath V; Khatri, Nilay; Joshi, Manjunath V; Joshi, Manjunath V; Joshi, Manjunath V; Joshi, Manjunath V; Joshi, Manjunath V; DA-IICT, Gandhinagar; Khatri, Nilay
    In this article, we propose a new regularization-based approach for pan-sharpening based on the concepts of self-similarity and Gabor prior. The given low spatial resolution (LR) and high spectral resolution multi-spectral (MS) image is modelled as degraded and noisy version of the unknown high spatial resolution (HR) version. Since this problem is ill-posed, we use regularization to obtain the final solution. In the proposed method, we first obtain an initial HR approximation of the unknown pan-sharpened image using self-similarity and sparse representation (SR) theory. Using self-similarity, we obtain the HR patches from the given LR observation by searching for matching patches in its coarser resolution, thereby obtaining LR�HR pairs. An SR framework is used to obtain the patch pairs for which no matches are available for the patches in LR observation. The entire set of matched HR patches constitutes initial HR approximation (initial estimate) to the final pan-sharpened image which is used to estimate the degradation matrix as used in our model. A regularization framework is then used to obtain the final solution in which we propose to use a new prior which we refer as Gabor prior that extracts the bandpass details from the registered panchromatic (Pan) image. In addition, we also include Markov random field (MRF) smoothness prior that preserves the smoothness in the final pan-sharpened image. MRF parameter is derived using the initial estimate image. The final cost function consists of data fitting term and two prior terms corresponding to Gabor and MRF. Since the derived cost function is convex, simple gradient-based method is used to obtain the final solution. The efficacy of the proposed method is evaluated by conducting the experiments on degraded as well as on un-degraded datasets of three different satellites, i.e., Ikonos-2, Quickbird, and Worldview-2. The results are compared on the basis of traditional measures as well as recently proposed quality with no reference (QNR) measure, which does not require the reference image.
  • Thumbnail Image
    PublicationMetadata only
    Auto-inpainting Heritage Scenes: a Complete Framework for Detecting and Infilling Cracks in Images and Videos with Quantitative Assessment
    (Springer, 01-04-2015) Padalkar, Milind G; Joshi, Manjunath V; Joshi, Manjunath V; Joshi, Manjunath V; Joshi, Manjunath V; Joshi, Manjunath V; Joshi, Manjunath V; DA-IICT, Gandhinagar; Padalkar, Milind G (201121015)
    The need for preservation of cultural heritage has necessitated the research on digitally repairing the photographs of damaged monuments. In this paper, we first propose a technique for automatically detecting the cracked regions in photographs of monuments. Unlike the usual practice of manually selecting the mask for inpainting, the detected regions are supplied to an inpainting algorithm. Thus, the process of digitally repairing the cracked regions that physical objects have, using inpainting, is completely automated. The detection of cracked regions is based on comparison of patches, for which we use a measure derived from the edit distance, which is a popular string metric used in the area of text mining. Further, we extend this method to perform inpainting of video frames by making use of the scale-invariant feature transform and homography. We consider the camera to move while capturing video of the heritage site, as such videos are typically captured by novices, hobbyists and tourists. Finally, we also propose a video quality measure to quantify the temporal consistency of the inpainted video. Experiments have been carried out on videos captured from the heritage site at Hampi, India.
  • Thumbnail Image
    PublicationMetadata only
    Multiresolution Image Fusion: Use of Compressive Sensing and Graph Cuts
    (IEEE, 01-05-2014) Harikumar, V; Gajjar, Prakash P; Joshi, Manjunath V; Raval, Mehul S; Joshi, Manjunath V; Joshi, Manjunath V; Joshi, Manjunath V; Joshi, Manjunath V; Joshi, Manjunath V; DA-IICT, Gandhinagar; Harikumar, V (201011016); Gajjar, Prakash P (200521004)
    In this paper, we propose a new approach for multiresolution fusion, i.e., obtaining a high spatial and spectral resolution multispectral (MS) image using the available low spatial resolution MS and the high spatial resolution Panchromatic (Pan) image. Our approach is based on the idea of compressive sensing (CS) and graph cuts. Assuming that both the MS and Pan images have the same sparseness, a close approximation to the MS image is obtained from the Pan image using the theory of compressive sensing and l1 minimization. We then use regularization framework to obtain fused image. The low resolution (LR) MS image is modeled as degraded and noisy version of fused image in which degradation matrix entires estimated using the close approximation are used. The regularization is carried out by using truncated quadratic smoothness prior which takes care of preservation of the discontinuities in the fused image. A suitable energy function is then formed consisting of data fitting term and prior term. Minimization of the energy function is carried out using a computationally efficient graph cuts optimization to obtain final fused image. Advantage of our approach is that the Pan and MS images need not be registered. This is because, we are not directly using the Pan digital numbers to derive the fused image. The effectiveness of the proposed method is illustrated by conducting experiments on real satellite images. Subjective and quantitative comparison of the proposed method with the state-of-the-art approaches indicates efficacy of our approach.
  • Thumbnail Image
    PublicationMetadata only
    Multiresolution image fusion using edge-preserving filters
    (SPIE, 01-07-2015) Upla, Kishor P; Joshi, Sharad; Joshi, Manjunath V; Gajjar, Prakash P; Joshi, Manjunath V; Joshi, Manjunath V; Joshi, Manjunath V; Joshi, Manjunath V; Joshi, Manjunath V; DA-IICT, Gandhinagar
    We propose two approaches of multiresolution image fusion using multistage guided filter and difference of Gaussians (DoGs). In a multiresolution image fusion problem, the given multispectral (MS) and panchromatic (Pan) images have high spectral and high spatial resolutions, respectively. One can obtain the fused image using these two images by injecting the missing high frequency details from the Pan image into the MS image. The quality of the final fused image will then depend on the method used for high frequency details extraction and also on the technique for injecting these details into the MS image. Specifically, we have chosen the guided filter and DoGs for detail extraction since these are more versatile in applications involving feature extraction, denoising, and so on. The detail extraction process in the fusion approach using a guided filter exploits the relationship between the Pan and MS images by utilizing one of them as a guidance image while extracting details from the other. The final fused image is obtained by adding the extracted high frequency details to the corresponding MS image. This way, the spatial distortion of the MS image is reduced by consistently combining the details obtained using both MS and Pan images. In the fusion method using DoGs, the high frequency details are extracted in the first and second levels by subtracting the blurred images of the original Pan. The extracted details at both DoGs are added to the MS image to obtain the final fused image. Advantages and disadvantages of each method are discussed and the comparison of the results is shown between the two. The results are also compared with the traditional and the state-of-the-art methods using the images captured using different satellites such as Quickbird, Ikonos-2, and Worldview-2. The quantitative assessment is evaluated using the conventional measures as well as using a relatively new index, i.e., quality with no reference which does not require a reference image. The results and measures clearly show that there is promising improvement in the quality of the fused image using the proposed approaches.