I had already send a doubt about 2D DWT. I send  brief explanation of my algorithm.

My algorithm is given below.

Noisy image ->high pass row filter ->{ high pass filtered output -------->down sampling------>high pass colom filter .....(1)

                                                     --> { low pass filtered output--------->down sampling -------->high pass colom filter .......(2)

....(1) { high pass colom filter output---->down sampling---->thresholding

....(1) {low pass colom filter output ---->down sampling---->thresholding

....(2) { high pass colom filter output ------->down sampling ----->thresholding

....(2) {low pass colom filter output------>down sampling -------->thresholding

low pass row/colom filter output =image (before the row/colomn high pass filter applied) - row/colomn  high pass filter output  .

In this filter there are four output cmponents

For reconstructing the orginal image the reverse operation is done.

My doubt is  how determine the   threshold value ? (if threshold value is high some image data is losed, if low some noise is there.)

The filtering is done in spatial domain.(using a mask)