||Wavelet coding has been shown to be better than Discrete Cosine Transform (DCT) in image processing. Moreover, it has the feature of scalability, which is involved in modern video standards. This work presents novel algorithms, namely 2-D Symmetric Mask-based Discrete Wavelet Transform (SMDWT), to improve the critical issue of the 2-D lifting-based discrete wavelet transform (LDWT), and then obtain the benefit of low latency, high-speed operation, and low temporal memory. The SMDWT also has the advantages of high-performance embedded periodic extension boundary treatment, regular signal coding, short critical path, reduced latency time, and independent subband coding processing. Moreover, the 2-D lifting-based DWT performance can also be easily improved by exploiting appropriate parallel method inherently in SMDWT. Comparing with the normal 2-D 5/3 integer lifting-based DWT, the proposed method significantly improves lifting-based latency and complexity in 2-D DWT without degradation in image quality. The algorithm can be applied to real-time image/video applications, such as JPEG 2000, MPEG-4 still texture coding, and Scalable Video Coding (SVC).