Fusion of SPOT5 multispectral and Ikonos panchromatic images

International audienceThe offer of high spectral and high spatial resolutions images has grown in the last decade. It is know possible to obtain data from different sources with different spatial and spec-tral resolutions. The field of data fusion of remotely sensed data grown also very fast in the last years. In this paper, an algorithm allowing the merging of SPOT 5 images and Ikonos images are proposed. This algorithm is based on the ARSIS concept and presents an implementation for a ratio of spatial resolution equal to 10. The ARSIS concept is first detailed. Then, the way of de-fining a new implementation based on this concept is presented, allowing to understand how to define new implementations and to develop new solutions based on this concept. The proposed algorithm is developed, describing the different steps for building a fused product from a SPOT 5 multispectral data at 10 m and from a IKONOS panchromatic data at 1 m. Some other methods are proposed. The evaluation of the quality of the different methods is achieved using a set of quantitative quality parameters. The visual quality of the products are evaluated by a set of inter-preters. Conclusions are drawn on the quality of the proposed products

Perbandingan Teknik Resampling Pada Citra Hasil Pan-Sharpening Untuk Pemetaan Penutup Lahan Dengan Menggunakan Klasifikasi Terselia Maximum Likelihood

Penelitian ini bertujuan untuk mengetahui penggunaan metode pan-sharpend guna ekstraksi penutup/penggunaan lahan khususnya klasifikasi berbasis piksel menggunakan metode maximum likelihood. Hal ini didasari karena penggunaan metode pan-sharpend dalam ekstraksi penutup/penggunaan lahan umumnya sebatas interpertasi visual saja, sehingga tujuan penelitian ini untuk melihat seberapa baik akurasi dari berbagai metetode pan-sharpend untuk klasifikasi berbasis piksel. Metode pan-sharpend yang digunakan dalam penelitian ini yaitu Hue Saturation Value (HSV), Brovey, Gram-Schmidt dan ‘Principal Component’ selain membandingkan metode pan-sharpend penelitian ini juga melihat pengaruh pemilihan metode interpolasi/resampling saat proses pan-sharpend. Metode resampling yang digunakan antara lain nearest neighbour, bilinear interpolation dan cubic convolution. Untuk data yang digunakan dalam penelitian ini yaitu citra ALOS AVNIR-2 dan ALOS PRISM yang direkam pada tanggal 20 Juni 2009. Hasil citra pan-sharpend dievaluasi seara kuantitatif menggunakan parameter bias of mean dan koefisien korelasi, hasil menunjukan bahwa metode Gram-Schmidt dan ‘Principal Component’ memiliki kualitas citra yang baik. Kelas penutup/penggunaan lahan yang dihasilkan melalui citra ALOS AVNIR-2 sebanyak 11 kelas sedangkan pada citra hasil pan-sharpend dihasilkan 15 kelas penutup lahan. Dari uji akurasi interpretasi dihasilkan metode yang memiliki akurasi interpertasi paling tinggi yaitu metode ‘Principal Component’ dengan teknik interpolasi resampling cubic convolution sebesar 81,697% sedangkan hasil uji akurasi interpretasi citra asli ALOS AVNIR-2 sebesar 82,23 %

Image Fusion - The ARSIS concept and some successful implementation schemes

International audienceThis article aims at explaining the ARSIS concept. By fusing two sets of images A and B, one with a high spatial resolution, the other with a low spatial resolution and different spectral bands, the ARSIS concept permits to synthesise the dataset B at the resolution of A that is as close as possible to reality. It is based on the assumption that the missing information is linked to the high frequencies in the sets A and B. It searches a relationship between the high frequencies in the multispectral set B and the set A and models this relationship. The general problem for the synthesis is presented first. The general properties of the fused product are given. Then, the ARSIS concept is discussed. The general scheme for the implementation of a method belonging to this concept is presented. Then, this article intends to help practitioners and researchers to better understand this concept through practical details about implementations. Two Multi-Scale Models are described as well as two Inter-Band Structure Models. They are applied to an Ikonos image as an illustration case. The fused products are assessed by the means of a known protocol comprising a series of qualitative and quantitative tests. The products are found of satisfactory quality. This case illustrates the differences existing between the various models, their advantages and limits. Tracks for future improvements are discussed

Super Resolution of Wavelet-Encoded Images and Videos

In this dissertation, we address the multiframe super resolution reconstruction problem for wavelet-encoded images and videos. The goal of multiframe super resolution is to obtain one or more high resolution images by fusing a sequence of degraded or aliased low resolution images of the same scene. Since the low resolution images may be unaligned, a registration step is required before super resolution reconstruction. Therefore, we first explore in-band (i.e. in the wavelet-domain) image registration; then, investigate super resolution. Our motivation for analyzing the image registration and super resolution problems in the wavelet domain is the growing trend in wavelet-encoded imaging, and wavelet-encoding for image/video compression. Due to drawbacks of widely used discrete cosine transform in image and video compression, a considerable amount of literature is devoted to wavelet-based methods. However, since wavelets are shift-variant, existing methods cannot utilize wavelet subbands efficiently. In order to overcome this drawback, we establish and explore the direct relationship between the subbands under a translational shift, for image registration and super resolution. We then employ our devised in-band methodology, in a motion compensated video compression framework, to demonstrate the effective usage of wavelet subbands. Super resolution can also be used as a post-processing step in video compression in order to decrease the size of the video files to be compressed, with downsampling added as a pre-processing step. Therefore, we present a video compression scheme that utilizes super resolution to reconstruct the high frequency information lost during downsampling. In addition, super resolution is a crucial post-processing step for satellite imagery, due to the fact that it is hard to update imaging devices after a satellite is launched. Thus, we also demonstrate the usage of our devised methods in enhancing resolution of pansharpened multispectral images