A Connectivity-Guided AdaptiveWavelet Transform (CGAWT) based mesh compres- sion algorithm is proposed. On the contrary to previous work, the proposed method uses 2D image processing tools for compressing the mesh models. The 3D models are ¯rst transformed to 2D images on a regular grid structure by performing orthogonal projections onto the image plane. This operation is computationally simpler than pa- rameterization. The neighborhood concept in projection images is di®erent from 2D images because two connected vertex can be projected to isolated pixels. Connectiv- ity data of the 3D model de¯nes the interpixel correlations in the projection image. Thus the wavelet transforms used in image processing do not give good results on this representation. CGAWT is de¯ned to take advantage of interpixel correlations in the image-like representation. Using the proposed transform the pixels in the detail subbands are predicted from their connected neighbors in the low-pass subbands of the wavelet transform. The resulting wavelet data is encoded using either \Set Parti- tioning In Hierarchical Trees" (SPIHT) or JPEG2000. SPIHT approach is progressive because di®erent resolutions of the mesh can be reconstructed from di®erent partitions of SPIHT bitstream. On the other hand, JPEG2000 approach is a single rate coder. The quantization of the wavelet coe±cients determines the quality of the reconstructed model in JPEG2000 approach. Simulations using di®erent basis functions show that lazy wavelet basis gives better results. The results are improved using the CGAWT with lazy wavelet ¯lterbanks. SPIHT based algorithm is observed to be superior to JPEG2000 based mesh coder and MPEG-3DGC in rate-distortion.