應用三維小波轉換於高光譜影像壓縮之研究

Hyperspectral Image Compression Using Three-dimensional Wavelet Transformation

施鴻冠(Hung-Kuan Shih) ； 曾義星(Yi-Hsing Tseng) ； 徐百輝(Pai-Hui Hsu)

《航測及遙測學刊》 6卷2期 (2001/06) Pp. 57-70

https://doi.org/10.6574/JPRS.2001.6(2).4

摘要

高光譜影像具有豐富的光譜資訊，但其龐大的資料量不利於資料的傳輸，影像壓縮是解決此問題的主要途徑。以目前二維影像壓縮法沿用於高光譜影像，未能有效擠壓波譜資訊之重複性。本文提出三維小波轉換壓縮法，同時探索空間及波譜維度之資訊重複性，達到高效率的高光譜影像壓縮。其步驟有三：三維小波轉換、最佳量化及Huffman編碼。以AVIRIS為實驗影像，探討不同的小波函數、小波分解層數和量化階數，對高光譜影像壓縮的壓縮量及回復品質進行評估分析。實驗成果顯示三維小波轉換壓縮法不但可輕易達到高壓縮比，又能維持原光譜影像在分類辨識上的使用效力。

關鍵字

遙感探測 ； 高光譜影像 ； 影像壓縮 ； 三維小波轉換

並列摘要

Hyperspectral images provide richer and finer spectral information than traditional multispectral images, however the volume of generated data is dramatically increased. Data compression will be essential for economical distribution when spaceborn hyperspectral data are regularly available. Contemporary techniques of image compression are mainly designed to explore the redundant information in the 2-D image space. It is awkward when they are applied to hyperspectral data. In this study, a 3-D wavelet transform is proposed to explore useful information in the spatial and spectral dimension simultaneously. The procedure proposed for hyperspectral image compression is mainly divided into three steps: 3-D wavelet transform, optimal quantization and Huffman coding. Various combinations of wavelet functions, decomposition levels and quantization intervals were experimented with an AVIRIS image. The decompressed images are evaluated objectively and subjectively, based on signal-to-noise ratio (SNR) and classification accuracy measures, respectively. The results indicate that 3-D wavelet transform is efficient for hyperspectral image compression and preserves the capability of the classification applications.

並列關鍵字

Remote sensing ； Hyperspectral Image ； Image Compression ； 3-D Wavelet Transformation